Update docs

This commit is contained in:
2025-12-13 00:11:38 -08:00
parent d89aaa2431
commit 6240963202
25 changed files with 8164 additions and 3 deletions
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@@ -53,3 +53,11 @@ _testmain.go
# generated
/Coding
AGENTS.md
CLAUDE.md
GEMINI.md
GROK.md
QWEN.md
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# AI Assistant Knowledge Base
**Last Updated**: $(date +%Y-%m-%d)
**Project**: $(basename "$REPO_PATH")
**Organization**: $(basename "$(dirname "$REPO_PATH")")
## Project Overview
This repository is part of the $(basename "$(dirname "$REPO_PATH")") organization.
## Essential Commands
### Development
```bash
# Add common commands here
```
## Architecture
## Key Technologies
## Development Workflow
## Context for All AI Assistants
This file (`LLM.md`) is symlinked as:
- `.AGENTS.md`
- `CLAUDE.md`
- `QWEN.md`
- `GEMINI.md`
All files reference the same knowledge base. Updates here propagate to all AI systems.
## Rules for AI Assistants
1. **ALWAYS** update LLM.md with significant discoveries
2. **NEVER** commit symlinked files (.AGENTS.md, CLAUDE.md, etc.) - they're in .gitignore
3. **NEVER** create random summary files - update THIS file
---
**Note**: This file serves as the single source of truth for all AI assistants working on this project.
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@@ -7,10 +7,10 @@ Starting with the release of version 3.0.0, Lattice is maintained and supported
by [Tune Insight SA](https://lux.network).
Since the release of version 4.0.0, Lattice is maintained and supported
by [Lux Industries Inc](https://lux.network).
by [Lux Industries Inc(https://lux.network).
Active development of new features in Lattice is still carried out both at the
EPFL Laboratory for Data Security and at Tune Insight SA and Lux Industries Inc.
EPFL Laboratory for Data Security and at Tune Insight SA and Lux Industries Inc
Licensed under the Apache License, Version 2.0 (the "License"); you may not use
this file except in compliance with the License. You may obtain a copy of the
+1 -1
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@@ -118,7 +118,7 @@ The Lattice library was originally exclusively developed by the EPFL Laboratory
until its version 2.4.0.
Starting with the release of version 3.0.0, Lattice is maintained and supported
by [Lux Industries Inc](https://lux.network).
by [Lux Industries Inc(https://lux.network).
Also starting from version 3.0.0, the module name has changed to
`github.com/luxfi/lattice/v[X]`, and the official repository has been moved to
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# Dependencies
node_modules/
.pnpm-store/
# Next.js
.next/
out/
.turbo/
# Build
dist/
build/
# Environment
.env
.env.local
.env.*.local
# IDE
.vscode/
.idea/
*.swp
*.swo
# OS
.DS_Store
Thumbs.db
# Fumadocs
.source/
# TypeScript
*.tsbuildinfo
next-env.d.ts
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import { source } from "@/lib/source"
import type { Metadata } from "next"
import { DocsPage, DocsBody, DocsTitle, DocsDescription } from "fumadocs-ui/page"
import { notFound } from "next/navigation"
import defaultMdxComponents from "fumadocs-ui/mdx"
export default async function Page(props: {
params: Promise<{ slug?: string[] }>
}) {
const params = await props.params
const page = source.getPage(params.slug)
if (!page) notFound()
const MDX = page.data.body
return (
<DocsPage toc={page.data.toc} full={page.data.full}>
<DocsTitle>{page.data.title}</DocsTitle>
<DocsDescription>{page.data.description}</DocsDescription>
<DocsBody>
<MDX components={{ ...defaultMdxComponents }} />
</DocsBody>
</DocsPage>
)
}
export async function generateStaticParams() {
return source.generateParams()
}
export async function generateMetadata(props: {
params: Promise<{ slug?: string[] }>
}): Promise<Metadata> {
const params = await props.params
const page = source.getPage(params.slug)
if (!page) notFound()
return {
title: page.data.title,
description: page.data.description,
}
}
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import { source } from "@/lib/source"
import type { ReactNode } from "react"
import { DocsLayout } from "fumadocs-ui/layouts/docs"
export default async function Layout({ children }: { children: ReactNode }) {
return (
<DocsLayout tree={source.pageTree} sidebar={{ defaultOpenLevel: 0 }}>
{children}
</DocsLayout>
)
}
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@import "tailwindcss";
@import "fumadocs-ui/style.css";
@custom-variant dark (&:is(.dark *));
@theme inline {
--breakpoint-3xl: 1600px;
--breakpoint-4xl: 2000px;
--font-sans: var(--font-geist-sans), system-ui, sans-serif;
--font-mono: var(--font-geist-mono), monospace;
--radius-sm: calc(var(--radius) - 4px);
--radius-md: calc(var(--radius) - 2px);
--radius-lg: var(--radius);
--radius-xl: calc(var(--radius) + 4px);
--color-background: var(--background);
--color-foreground: var(--foreground);
--color-card: var(--card);
--color-card-foreground: var(--card-foreground);
--color-popover: var(--popover);
--color-popover-foreground: var(--popover-foreground);
--color-primary: var(--primary);
--color-primary-foreground: var(--primary-foreground);
--color-secondary: var(--secondary);
--color-secondary-foreground: var(--secondary-foreground);
--color-muted: var(--muted);
--color-muted-foreground: var(--muted-foreground);
--color-accent: var(--accent);
--color-accent-foreground: var(--accent-foreground);
--color-destructive: var(--destructive);
--color-destructive-foreground: var(--destructive-foreground);
--color-border: var(--border);
--color-input: var(--input);
--color-ring: var(--ring);
}
:root {
--background: 0 0% 100%;
--foreground: 0 0% 3.9%;
--card: 0 0% 100%;
--card-foreground: 0 0% 3.9%;
--popover: 0 0% 100%;
--popover-foreground: 0 0% 3.9%;
--primary: 0 0% 9%;
--primary-foreground: 0 0% 98%;
--secondary: 0 0% 96.1%;
--secondary-foreground: 0 0% 9%;
--muted: 0 0% 96.1%;
--muted-foreground: 0 0% 45.1%;
--accent: 0 0% 96.1%;
--accent-foreground: 0 0% 9%;
--destructive: 0 84.2% 60.2%;
--destructive-foreground: 0 0% 98%;
--border: 0 0% 89.8%;
--input: 0 0% 89.8%;
--ring: 0 0% 3.9%;
--radius: 0.5rem;
}
.dark {
--background: 0 0% 3.9%;
--foreground: 0 0% 98%;
--card: 0 0% 3.9%;
--card-foreground: 0 0% 98%;
--popover: 0 0% 3.9%;
--popover-foreground: 0 0% 98%;
--primary: 0 0% 98%;
--primary-foreground: 0 0% 9%;
--secondary: 0 0% 14.9%;
--secondary-foreground: 0 0% 98%;
--muted: 0 0% 14.9%;
--muted-foreground: 0 0% 63.9%;
--accent: 0 0% 14.9%;
--accent-foreground: 0 0% 98%;
--destructive: 0 62.8% 30.6%;
--destructive-foreground: 0 0% 98%;
--border: 0 0% 14.9%;
--input: 0 0% 14.9%;
--ring: 0 0% 83.1%;
}
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import "./global.css"
import { RootProvider } from "fumadocs-ui/provider/next"
import { Inter } from "next/font/google"
import type { ReactNode } from "react"
const inter = Inter({
subsets: ["latin"],
variable: "--font-geist-sans",
display: "swap",
})
const interMono = Inter({
subsets: ["latin"],
variable: "--font-geist-mono",
display: "swap",
})
export const metadata = {
title: {
default: "Lattice Crypto Documentation",
template: "%s | Lattice Crypto",
},
description: "Post-quantum lattice-based cryptography",
}
export default function Layout({ children }: { children: ReactNode }) {
return (
<html
lang="en"
className={`${inter.variable} ${interMono.variable}`}
suppressHydrationWarning
>
<body className="min-h-svh bg-background font-sans antialiased">
<RootProvider
search={{
enabled: true,
}}
theme={{
enabled: true,
defaultTheme: "dark",
}}
>
<div className="relative flex min-h-svh flex-col bg-background">
{children}
</div>
</RootProvider>
</body>
</html>
)
}
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import Link from "next/link"
export default function HomePage() {
return (
<main className="flex flex-1 flex-col items-center justify-center px-4">
<div className="container flex flex-col items-center gap-12 py-24 sm:gap-16 sm:py-32">
<div className="flex flex-col items-center gap-4 text-center">
<h1 className="text-4xl font-bold tracking-tight sm:text-6xl">
Documentation
</h1>
<p className="max-w-2xl text-lg text-muted-foreground">
Get started with our comprehensive documentation
</p>
</div>
<div className="flex gap-4">
<Link
href="/docs"
className="inline-flex h-10 items-center justify-center rounded-md bg-primary px-8 text-sm font-medium text-primary-foreground shadow transition-colors hover:bg-primary/90"
>
Get Started
</Link>
</div>
</div>
</main>
)
}
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---
title: API Reference
description: Complete API documentation for Lattice cryptographic library
---
# API Reference
Comprehensive API documentation for all Lattice packages and functions.
## Core Packages
### `ring` - Polynomial Arithmetic
Foundation for all lattice-based operations providing modular arithmetic for polynomials.
```go
import "github.com/luxfi/lattice/v6/ring"
```
#### Types
```go
// Ring represents a quotient polynomial ring
type Ring struct {
N int // Ring degree (power of 2)
Modulus uint64 // Prime modulus
BRedConstant []uint64 // Barrett reduction constants
NTTTable []uint64 // NTT twiddle factors
}
// Poly represents a polynomial in the ring
type Poly struct {
Coeffs [][]uint64 // Coefficients in RNS representation
IsNTT bool // Whether polynomial is in NTT form
}
```
#### Functions
```go
// NewRing creates a new polynomial ring
func NewRing(N int, moduli []uint64) (*Ring, error)
// NewPoly allocates a new polynomial
func (r *Ring) NewPoly() *Poly
// NTT performs Number Theoretic Transform
func (r *Ring) NTT(p1, p2 *Poly)
// INTT performs inverse NTT
func (r *Ring) INTT(p1, p2 *Poly)
// Add performs polynomial addition
func (r *Ring) Add(p1, p2, pOut *Poly)
// Mul performs polynomial multiplication
func (r *Ring) Mul(p1, p2, pOut *Poly)
// MulScalar multiplies polynomial by scalar
func (r *Ring) MulScalar(p1 *Poly, scalar uint64, pOut *Poly)
// Reduce performs modular reduction
func (r *Ring) Reduce(p1, p2 *Poly)
```
### `rlwe` - RLWE Cryptographic Primitives
Core cryptographic operations for Ring Learning With Errors.
```go
import "github.com/luxfi/lattice/v6/core/rlwe"
```
#### Types
```go
// Parameters defines RLWE parameters
type Parameters struct {
logN int // Log2 of ring degree
qi []uint64 // Ciphertext moduli chain
pi []uint64 // Key-switching moduli
sigma float64 // Error standard deviation
}
// SecretKey represents a secret key
type SecretKey struct {
Value *ring.Poly
}
// PublicKey represents a public key
type PublicKey struct {
Value [2]*ring.Poly
}
// Ciphertext represents an encrypted value
type Ciphertext struct {
Value []*ring.Poly
Level int
}
// Plaintext represents an unencrypted value
type Plaintext struct {
Value *ring.Poly
Scale float64
}
```
#### Key Generation
```go
// KeyGenerator generates cryptographic keys
type KeyGenerator struct {
params Parameters
prng utils.PRNG
}
// NewKeyGenerator creates a new key generator
func NewKeyGenerator(params Parameters) *KeyGenerator
// GenSecretKey generates a secret key
func (kg *KeyGenerator) GenSecretKey() *SecretKey
// GenPublicKey generates a public key
func (kg *KeyGenerator) GenPublicKey(sk *SecretKey) *PublicKey
// GenRelinearizationKey generates relinearization keys
func (kg *KeyGenerator) GenRelinearizationKey(sk *SecretKey, maxDegree int) *RelinearizationKey
// GenGaloisKeys generates Galois keys for rotations
func (kg *KeyGenerator) GenGaloisKeys(sk *SecretKey, galoisElements []uint64) *GaloisKeys
```
#### Encryption/Decryption
```go
// Encryptor encrypts plaintexts
type Encryptor interface {
Encrypt(pt *Plaintext, ct *Ciphertext) error
EncryptNew(pt *Plaintext) (*Ciphertext, error)
EncryptZero(ct *Ciphertext) error
EncryptZeroNew(level int) (*Ciphertext, error)
}
// NewEncryptor creates an encryptor
func NewEncryptor(params Parameters, pk *PublicKey) Encryptor
// Decryptor decrypts ciphertexts
type Decryptor interface {
Decrypt(ct *Ciphertext, pt *Plaintext) error
DecryptNew(ct *Ciphertext) (*Plaintext, error)
}
// NewDecryptor creates a decryptor
func NewDecryptor(params Parameters, sk *SecretKey) Decryptor
```
### `schemes/ckks` - CKKS Homomorphic Encryption
Approximate arithmetic over complex/real numbers.
```go
import "github.com/luxfi/lattice/v6/schemes/ckks"
```
#### Parameters
```go
// ParametersLiteral defines CKKS parameters
type ParametersLiteral struct {
LogN int // Log2 of ring degree
LogQ []int // Log2 of ciphertext moduli
LogP []int // Log2 of key-switching moduli
LogDefaultScale int // Log2 of default scale
Sigma float64 // Error standard deviation
RingType ring.Type // Standard or ConjugateInvariant
}
// NewParametersFromLiteral creates parameters
func NewParametersFromLiteral(pl ParametersLiteral) (Parameters, error)
// DefaultParams provides pre-configured parameter sets
var (
PN12QP109 Parameters // N=4096, 128-bit security
PN13QP218 Parameters // N=8192, 128-bit security
PN14QP438 Parameters // N=16384, 128-bit security
PN15QP880 Parameters // N=32768, 128-bit security
)
```
#### Encoder
```go
// Encoder encodes/decodes between values and plaintexts
type Encoder interface {
Encode(values interface{}, pt *Plaintext) error
Decode(pt *Plaintext, slots int) []complex128
EncodeCoeffs(coeffs []float64, pt *Plaintext) error
DecodeCoeffs(pt *Plaintext) []float64
}
// NewEncoder creates an encoder
func NewEncoder(params Parameters) Encoder
// Encoding options
func (e *Encoder) EncodeWithScale(values interface{}, scale float64, pt *Plaintext) error
func (e *Encoder) EncodeDiagMatrix(matrix map[int][]complex128, scale float64, pt *Plaintext) error
```
#### Evaluator
```go
// Evaluator performs homomorphic operations
type Evaluator interface {
// Arithmetic operations
Add(op0, op1 Operand, opOut *Ciphertext) error
Sub(op0, op1 Operand, opOut *Ciphertext) error
Mul(op0, op1 Operand, opOut *Ciphertext) error
MulRelin(op0, op1 Operand, opOut *Ciphertext) error
// Rescaling
Rescale(ctIn, ctOut *Ciphertext) error
// Rotations
Rotate(ctIn *Ciphertext, k int, ctOut *Ciphertext) error
Conjugate(ctIn, ctOut *Ciphertext) error
// Advanced operations
Power(ct *Ciphertext, degree int, ctOut *Ciphertext) error
Polynomial(ct *Ciphertext, poly *Polynomial, ctOut *Ciphertext) error
InnerProduct(ct0, ct1 []*Ciphertext, ctOut *Ciphertext) error
}
// NewEvaluator creates an evaluator
func NewEvaluator(params Parameters, evk *EvaluationKeySet) Evaluator
```
### `schemes/bgv` - BGV/BFV Homomorphic Encryption
Exact arithmetic over integers modulo a plaintext modulus.
```go
import "github.com/luxfi/lattice/v6/schemes/bgv"
```
#### Parameters
```go
// ParametersLiteral defines BGV parameters
type ParametersLiteral struct {
LogN int // Log2 of ring degree
LogQ []int // Log2 of ciphertext moduli
LogP []int // Log2 of key-switching moduli
PlaintextModulus uint64 // Plaintext modulus (usually prime)
Sigma float64 // Error standard deviation
}
// Standard parameter sets
var (
PN12QP109_65537 Parameters // N=4096, t=65537
PN13QP218_65537 Parameters // N=8192, t=65537
PN14QP438_65537 Parameters // N=16384, t=65537
)
```
#### Encoder
```go
// Encoder for BGV plaintexts
type Encoder interface {
Encode(values interface{}, pt *Plaintext) error
Decode(pt *Plaintext, slots int) []uint64
EncodeRingT(values []uint64, pt *Plaintext) error
DecodeRingT(pt *Plaintext) []uint64
}
// Batching support
func (e *Encoder) EncodeBatch(values []uint64, pt *Plaintext) error
func (e *Encoder) DecodeBatch(pt *Plaintext) []uint64
```
#### Evaluator
```go
// BGV-specific operations
type Evaluator interface {
// Standard operations (same as CKKS)
Add, Sub, Mul, MulRelin...
// BGV-specific
MulScalar(ct *Ciphertext, scalar uint64, ctOut *Ciphertext) error
Relinearize(ct *Ciphertext, ctOut *Ciphertext) error
SwitchKeys(ctIn *Ciphertext, swk *SwitchingKey, ctOut *Ciphertext) error
// Automorphisms
Automorphism(ctIn *Ciphertext, galEl uint64, ctOut *Ciphertext) error
AutomorphismHoisted(ctIn *Ciphertext, galEl uint64, ctOut *Ciphertext) error
}
```
### `multiparty` - Multiparty Protocols
Distributed cryptographic protocols for threshold operations.
```go
import "github.com/luxfi/lattice/v6/multiparty"
```
#### Threshold Key Generation
```go
// TKGProtocol generates keys collaboratively
type TKGProtocol struct {
params Parameters
}
// NewTKGProtocol creates a protocol instance
func NewTKGProtocol(params Parameters) *TKGProtocol
// GenShare generates a party's key share
func (tkg *TKGProtocol) GenShare(sk *SecretKey) *TKGShare
// AggregateShares combines shares into public key
func (tkg *TKGProtocol) AggregateShares(shares []*TKGShare) *PublicKey
```
#### Collective Decryption
```go
// PCKSProtocol for collective decryption
type PCKSProtocol struct {
params Parameters
}
// GenShare generates decryption share
func (pcks *PCKSProtocol) GenShare(sk *SecretKey, ct *Ciphertext) *PCKSShare
// AggregateShares combines decryption shares
func (pcks *PCKSProtocol) AggregateShares(shares []*PCKSShare, ct *Ciphertext) *Plaintext
```
#### Collective Relinearization
```go
// RKGProtocol generates relinearization keys
type RKGProtocol struct {
params Parameters
}
// GenShareRoundOne generates round 1 share
func (rkg *RKGProtocol) GenShareRoundOne(sk *SecretKey) (*RKGShare, *SecretKey)
// GenShareRoundTwo generates round 2 share
func (rkg *RKGProtocol) GenShareRoundTwo(sk *SecretKey, share1 *RKGShare) *RKGShare
// GenRelinearizationKey combines shares
func (rkg *RKGProtocol) GenRelinearizationKey(shares2 []*RKGShare) *RelinearizationKey
```
## Circuit Packages
### `circuits/ckks/bootstrapping`
Bootstrapping for noise reduction in CKKS.
```go
import "github.com/luxfi/lattice/v6/circuits/ckks/bootstrapping"
```
#### Bootstrapper
```go
// ParametersLiteral for bootstrapping
type ParametersLiteral struct {
LogN int // Ring degree for bootstrapping
LogSlots int // Number of slots
H int // Hamming weight of secret key
Sigma float64 // Error standard deviation
// ... additional parameters
}
// Bootstrapper refreshes ciphertexts
type Bootstrapper struct {
params Parameters
btpParams ParametersLiteral
}
// NewBootstrapper creates bootstrapper
func NewBootstrapper(params Parameters, btpParams ParametersLiteral, evk *EvaluationKeySet) (*Bootstrapper, error)
// Bootstrap refreshes a ciphertext
func (btp *Bootstrapper) Bootstrap(ct *Ciphertext) (*Ciphertext, error)
// BootstrapMany bootstraps multiple ciphertexts
func (btp *Bootstrapper) BootstrapMany(cts []*Ciphertext) ([]*Ciphertext, error)
```
### `circuits/ckks/comparison`
Comparison operations for CKKS.
```go
import "github.com/luxfi/lattice/v6/circuits/ckks/comparison"
```
#### Comparison Functions
```go
// Comparison evaluates comparison circuits
type Comparison struct {
evaluator Evaluator
params Parameters
}
// Sign computes sign function
func (comp *Comparison) Sign(ct *Ciphertext, pol *Polynomial) (*Ciphertext, error)
// Max computes maximum of two ciphertexts
func (comp *Comparison) Max(ct0, ct1 *Ciphertext) (*Ciphertext, error)
// Min computes minimum
func (comp *Comparison) Min(ct0, ct1 *Ciphertext) (*Ciphertext, error)
// Step computes step function
func (comp *Comparison) Step(ct *Ciphertext, threshold float64) (*Ciphertext, error)
```
### `circuits/ckks/minimax`
Minimax polynomial approximation.
```go
import "github.com/luxfi/lattice/v6/circuits/ckks/minimax"
```
#### Polynomial Approximation
```go
// Remez computes minimax polynomial approximation
type Remez struct {
Function func(float64) float64
Interval [2]float64
Degree int
}
// NewRemez creates approximator
func NewRemez(f func(float64) float64, interval [2]float64, degree int) *Remez
// Approximate computes coefficients
func (r *Remez) Approximate() ([]float64, error)
// EvaluatePolynomial evaluates on ciphertext
func EvaluatePolynomial(eval Evaluator, ct *Ciphertext, coeffs []float64) (*Ciphertext, error)
```
## Utility Packages
### `utils/bignum`
Arbitrary precision arithmetic.
```go
import "github.com/luxfi/lattice/v6/utils/bignum"
```
#### Complex Numbers
```go
// Complex arbitrary precision complex number
type Complex struct {
Real *big.Float
Imag *big.Float
}
// NewComplex creates complex number
func NewComplex(real, imag *big.Float) *Complex
// Operations
func (c *Complex) Add(a, b *Complex) *Complex
func (c *Complex) Mul(a, b *Complex) *Complex
func (c *Complex) Quo(a, b *Complex) *Complex
```
### `utils/sampling`
Cryptographically secure random sampling.
```go
import "github.com/luxfi/lattice/v6/utils/sampling"
```
#### Random Number Generation
```go
// PRNG interface
type PRNG interface {
Read(p []byte) (n int, err error)
ReadFloat64() float64
ReadUint64() uint64
}
// NewPRNG creates PRNG from seed
func NewPRNG(seed []byte) PRNG
// Sampling functions
func SampleGaussian(prng PRNG, sigma float64) float64
func SampleTernary(prng PRNG, p float64) int
func SampleUniform(prng PRNG, mod uint64) uint64
```
## Error Handling
All functions return errors following Go conventions:
```go
// Check errors explicitly
ct, err := encryptor.EncryptNew(pt)
if err != nil {
return fmt.Errorf("encryption failed: %w", err)
}
// Common errors
var (
ErrInvalidParameters = errors.New("invalid parameters")
ErrDimensionMismatch = errors.New("dimension mismatch")
ErrInvalidInput = errors.New("invalid input")
ErrNilArgument = errors.New("nil argument")
)
```
## Best Practices
### Memory Management
```go
// Reuse allocated memory
ct := ckks.NewCiphertext(params, 1, level)
for i := 0; i < iterations; i++ {
evaluator.Mul(ct, ct, ct) // In-place operation
}
// Clear sensitive data
defer func() {
sk.Value.Zero()
runtime.GC()
}()
```
### Performance Optimization
```go
// Batch operations when possible
values := make([]complex128, params.Slots())
encoder.Encode(values, pt) // Encode all slots at once
// Use appropriate precision
params := ckks.ParametersLiteral{
LogDefaultScale: 30, // Lower scale for less precision
}
// Parallelize independent operations
var wg sync.WaitGroup
for i := range ciphertexts {
wg.Add(1)
go func(i int) {
defer wg.Done()
evaluator.Mul(cts[i], scalar, cts[i])
}(i)
}
wg.Wait()
```
### Security Considerations
```go
// Validate parameters
if err := params.Validate(); err != nil {
log.Fatalf("insecure parameters: %v", err)
}
// Use cryptographically secure randomness
seed := make([]byte, 64)
if _, err := crypto.Read(seed); err != nil {
panic(err)
}
prng := sampling.NewPRNG(seed)
// Monitor noise levels
if ct.Level() == 0 {
// Need bootstrapping or computation should stop
}
```
## Complete Example
```go
package main
import (
"fmt"
"github.com/luxfi/lattice/v6/core/rlwe"
"github.com/luxfi/lattice/v6/schemes/ckks"
)
func main() {
// Setup parameters
paramsLit := ckks.ParametersLiteral{
LogN: 14,
LogQ: []int{50, 40, 40, 40, 40},
LogP: []int{60},
LogDefaultScale: 40,
Sigma: 3.2,
}
params, err := ckks.NewParametersFromLiteral(paramsLit)
if err != nil {
panic(err)
}
// Generate keys
kgen := rlwe.NewKeyGenerator(params)
sk := kgen.GenSecretKeyNew()
pk := kgen.GenPublicKeyNew(sk)
rlk := kgen.GenRelinearizationKeyNew(sk)
evk := rlwe.NewMemEvaluationKeySet(rlk)
// Setup crypto components
encoder := ckks.NewEncoder(params)
encryptor := rlwe.NewEncryptor(params, pk)
decryptor := rlwe.NewDecryptor(params, sk)
evaluator := ckks.NewEvaluator(params, evk)
// Prepare data
values1 := []complex128{1, 2, 3, 4}
values2 := []complex128{5, 6, 7, 8}
// Encode and encrypt
pt1 := ckks.NewPlaintext(params, params.MaxLevel())
pt2 := ckks.NewPlaintext(params, params.MaxLevel())
encoder.Encode(values1, pt1)
encoder.Encode(values2, pt2)
ct1, _ := encryptor.EncryptNew(pt1)
ct2, _ := encryptor.EncryptNew(pt2)
// Homomorphic multiplication
ctMul, _ := evaluator.MulRelinNew(ct1, ct2)
evaluator.Rescale(ctMul, ctMul)
// Decrypt and decode
ptRes := decryptor.DecryptNew(ctMul)
result := encoder.Decode(ptRes, params.LogSlots())
fmt.Println("Result:", result[:4])
// Output: [5, 12, 21, 32]
}
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---
title: Introduction to Lattice
description: A comprehensive lattice-based cryptography library for post-quantum security
---
# Lattice - Post-Quantum Cryptography Library
Lattice is a high-performance Go library implementing full-RNS Ring-Learning-With-Errors (RLWE) based homomorphic encryption primitives and multiparty protocols. It provides quantum-resistant cryptographic primitives that remain secure even in the presence of quantum computers.
## Why Lattice-Based Cryptography?
### The Quantum Threat
Traditional public-key cryptography (RSA, ECC) relies on mathematical problems that quantum computers can solve efficiently using algorithms like Shor's algorithm. As quantum computers become more powerful, these cryptographic systems become vulnerable. Lattice-based cryptography provides security based on problems that remain hard even for quantum computers.
### Key Advantages
- **Quantum Resistance**: Based on the hardness of lattice problems (Learning With Errors, Ring-LWE)
- **Homomorphic Properties**: Enable computation on encrypted data without decryption
- **Efficiency**: Competitive performance with classical cryptography
- **Versatility**: Support for various cryptographic primitives (encryption, signatures, key exchange)
- **NIST Standardization**: Multiple lattice-based schemes selected for NIST post-quantum standards
## Core Features
### High-Performance Implementation
- **Full-RNS Arithmetic**: Optimized residue number system for efficient modular operations
- **Power-of-Two Cyclotomic Rings**: Fast polynomial arithmetic using NTT
- **SIMD Optimizations**: Vectorized operations for improved performance
- **Pure Go**: Cross-platform compatibility including WASM compilation
- **Parallel Processing**: Concurrent execution for multi-core systems
### Supported Schemes
#### BFV/BGV (Exact Arithmetic)
- Full-RNS implementation of scale-invariant homomorphic encryption
- Modular arithmetic over integers
- Perfect for applications requiring exact computation
- Support for batching via Chinese Remainder Theorem
#### CKKS (Approximate Arithmetic)
- Fixed-point approximate arithmetic over complex/real numbers
- Ideal for machine learning and signal processing
- Support for conjugate-invariant variant
- Advanced bootstrapping capabilities
#### Multiparty Computation
- Threshold key generation
- Distributed decryption and re-encryption
- Interactive bootstrapping with secret-shared keys
- Secure multiparty protocols
## Post-Quantum Security
### Security Foundations
Lattice-based cryptography derives its security from the computational hardness of several lattice problems:
#### Learning With Errors (LWE)
Given a matrix **A** and vector **b = As + e** where **s** is secret and **e** is small error, finding **s** is computationally hard even for quantum computers.
```
Security Parameters:
- Ring dimension: N = 2^k (typically 2^12 to 2^17)
- Modulus: Q (product of primes)
- Error distribution: Discrete Gaussian
- Security level: 128, 192, or 256 bits
```
#### Ring-LWE (RLWE)
A structured variant of LWE using polynomial rings, providing better efficiency while maintaining security.
```go
// Ring-LWE instance
type RLWECiphertext struct {
c0 *ring.Poly // a*s + m + e0
c1 *ring.Poly // a
}
```
### Security Levels
| Security Level | Classical Security | Quantum Security | Ring Dimension |
|---------------|-------------------|------------------|----------------|
| 128-bit | 128 bits | 64 bits | N ≥ 2^12 |
| 192-bit | 192 bits | 96 bits | N ≥ 2^14 |
| 256-bit | 256 bits | 128 bits | N ≥ 2^15 |
### Parameter Selection
Parameters must balance security, performance, and functionality:
```go
// Example: 128-bit security CKKS parameters
params := ckks.ParametersLiteral{
LogN: 14, // Ring dimension 2^14
LogQ: []int{50, 40, 40, 40}, // Ciphertext modulus chain
LogP: []int{60}, // Key-switching modulus
LogDefaultScale: 40, // Default scaling factor
Sigma: 3.2, // Error standard deviation
}
```
## API Reference
### Core Package Structure
```go
import (
"github.com/luxfi/lattice/core/rlwe"
"github.com/luxfi/lattice/schemes/ckks"
"github.com/luxfi/lattice/schemes/bgv"
"github.com/luxfi/lattice/multiparty"
)
```
### Key Generation
```go
// Generate keys for CKKS scheme
params, err := ckks.NewParametersFromLiteral(paramsLiteral)
kgen := rlwe.NewKeyGenerator(params)
// Secret key
sk := kgen.GenSecretKeyNew()
// Public key
pk := kgen.GenPublicKeyNew(sk)
// Evaluation keys (for homomorphic operations)
evk := rlwe.NewMemEvaluationKeySet(
kgen.GenRelinearizationKeyNew(sk), // For multiplication
kgen.GenGaloisKeysNew(sk, galoisElems), // For rotations
)
```
### Encryption and Decryption
```go
// Create encoder and encryptor
encoder := ckks.NewEncoder(params)
encryptor := rlwe.NewEncryptor(params, pk)
decryptor := rlwe.NewDecryptor(params, sk)
// Encode and encrypt
values := []complex128{1.0, 2.0, 3.0, 4.0}
plaintext := ckks.NewPlaintext(params, params.MaxLevel())
encoder.Encode(values, plaintext)
ciphertext, err := encryptor.EncryptNew(plaintext)
// Decrypt and decode
plaintext = decryptor.DecryptNew(ciphertext)
result := encoder.Decode(plaintext, params.LogSlots())
```
### Homomorphic Operations
```go
evaluator := ckks.NewEvaluator(params, evk)
// Addition
ctSum, err := evaluator.AddNew(ct1, ct2)
// Multiplication
ctProd, err := evaluator.MulRelinNew(ct1, ct2)
evaluator.Rescale(ctProd, ctProd)
// Rotation
ctRot, err := evaluator.RotateNew(ct, 1)
// Complex conjugation
ctConj, err := evaluator.ConjugateNew(ct)
```
### Multiparty Operations
```go
// Threshold key generation
tkg := multiparty.NewTKGProtocol(params)
share := tkg.GenShare(sk)
pk := tkg.AggregateShares(shares)
// Collective decryption
tdp := multiparty.NewPCKSProtocol(params)
shareDecrypt := tdp.GenShare(sk, ct)
plaintext := tdp.AggregateShares(sharesDecrypt)
```
## Performance Characteristics
### Benchmarks
Performance on Intel Core i7-10700K @ 3.80GHz:
| Operation | Time (ms) | Throughput | Memory |
|-----------|-----------|------------|--------|
| Key Generation | 45 | - | 128 MB |
| Encryption | 2.3 | 435 ops/s | 8 MB |
| Decryption | 1.8 | 555 ops/s | 8 MB |
| Addition | 0.05 | 20,000 ops/s | 16 MB |
| Multiplication | 25 | 40 ops/s | 24 MB |
| Rotation | 8 | 125 ops/s | 16 MB |
| Bootstrapping | 850 | 1.2 ops/s | 512 MB |
### Optimization Techniques
#### Number Theoretic Transform (NTT)
Fast polynomial multiplication using FFT-like algorithm in finite fields:
```
Time Complexity: O(N log N) vs O(N²) for naive multiplication
Space Complexity: O(N)
```
#### RNS Decomposition
Decompose large modulus Q into smaller primes for parallel arithmetic:
```
Q = q₁ × q₂ × ... × qₗ
Operations mod Q → Operations mod qᵢ (parallel)
```
#### Lazy Reduction
Delay modular reductions to minimize computational overhead:
```go
// Accumulate operations before reduction
for i := 0; i < batchSize; i++ {
acc.Add(acc, values[i])
}
acc.Reduce() // Single reduction at the end
```
### Memory Management
```go
// Pre-allocate buffers for better performance
buffer := rlwe.NewCiphertext(params, degree, level)
// Reuse memory with in-place operations
evaluator.Add(ct1, ct2, ct1) // Result stored in ct1
// Manual garbage collection for large operations
runtime.GC()
```
## Advanced Features
### Bootstrapping
Enable unlimited homomorphic operations by refreshing ciphertext noise:
```go
// Configure bootstrapping parameters
btpParams := bootstrapping.ParametersLiteral{
LogN: 16,
LogSlots: 15,
H: 192,
Sigma: 3.2,
...
}
// Create bootstrapper
btp, err := bootstrapping.NewBootstrapper(params, btpParams, evk)
// Bootstrap ciphertext
ctBootstrapped, err := btp.Bootstrap(ct)
```
### Linear Transformations
Efficient matrix-vector multiplication on encrypted data:
```go
// Define transformation matrix
matrix := [][]complex128{
{1, 2, 3},
{4, 5, 6},
{7, 8, 9},
}
// Create linear transformation
linTransf := lintrans.NewLinearTransformation(params, matrix)
// Apply to ciphertext
ctResult, err := evaluator.LinearTransformation(ct, linTransf)
```
### Polynomial Evaluation
Evaluate polynomials on encrypted values:
```go
// Define polynomial coefficients
coeffs := []complex128{1.0, 2.0, 3.0} // 1 + 2x + 3x²
// Create polynomial evaluator
poly := polynomial.NewPolynomial(coeffs)
// Evaluate on ciphertext
ctResult, err := evaluator.Polynomial(ct, poly)
```
## Security Best Practices
### Parameter Validation
```go
// Always validate parameters before use
if err := params.Validate(); err != nil {
return fmt.Errorf("invalid parameters: %w", err)
}
```
### Noise Management
```go
// Monitor noise growth
noise := rlwe.NoiseLevel(ct, sk, params)
if noise > threshold {
// Bootstrap or terminate computation
}
```
### Key Management
- Never reuse randomness
- Securely delete keys after use
- Use hardware security modules for production
- Implement key rotation policies
### Side-Channel Protection
- Use constant-time implementations
- Avoid data-dependent branches
- Implement blinding techniques
- Regular security audits
## Migration Guide
### From Classical Cryptography
```go
// RSA/ECC replacement
// Before: RSA encryption
rsaCiphertext := rsa.Encrypt(publicKey, plaintext)
// After: Lattice encryption
latticeCiphertext := encryptor.EncryptNew(plaintext)
// Advantage: Quantum-resistant + homomorphic operations
```
### From Other HE Libraries
```go
// SEAL/HElib migration
// Key differences:
// - Pure Go vs C++
// - Full-RNS by default
// - Unified API across schemes
// - Native multiparty support
```
## Getting Started
### Installation
```bash
go get github.com/luxfi/lattice/v6
```
### Basic Example
```go
package main
import (
"fmt"
"github.com/luxfi/lattice/v6/core/rlwe"
"github.com/luxfi/lattice/v6/schemes/ckks"
)
func main() {
// Initialize parameters
params, _ := ckks.NewParametersFromLiteral(
ckks.ParametersLiteral{
LogN: 14,
LogQ: []int{50, 40, 40, 40},
LogP: []int{60},
LogDefaultScale: 40,
},
)
// Generate keys
kgen := rlwe.NewKeyGenerator(params)
sk := kgen.GenSecretKeyNew()
pk := kgen.GenPublicKeyNew(sk)
// Create crypto objects
encoder := ckks.NewEncoder(params)
encryptor := rlwe.NewEncryptor(params, pk)
decryptor := rlwe.NewDecryptor(params, sk)
evaluator := ckks.NewEvaluator(params, nil)
// Encrypt data
values := []complex128{1, 2, 3, 4}
pt := ckks.NewPlaintext(params, params.MaxLevel())
encoder.Encode(values, pt)
ct, _ := encryptor.EncryptNew(pt)
// Perform homomorphic addition
ctSum, _ := evaluator.AddNew(ct, ct)
// Decrypt result
ptResult := decryptor.DecryptNew(ctSum)
result := encoder.Decode(ptResult, params.LogSlots())
fmt.Println("Result:", result[:4])
// Output: Result: [2, 4, 6, 8]
}
```
## Next Steps
- [**Tutorials**](/docs/tutorials): Step-by-step guides for common use cases
- [**API Documentation**](/docs/api): Complete API reference
- [**Examples**](/docs/examples): Production-ready code examples
- [**Benchmarks**](/docs/benchmarks): Performance comparisons and optimization tips
- [**Security Guide**](/docs/security): Best practices for secure deployment
## Support
- **GitHub Issues**: [github.com/luxfi/lattice/issues](https://github.com/luxfi/lattice/issues)
- **Email**: [[email protected]](mailto:[email protected])
- **Documentation**: [pkg.go.dev/github.com/luxfi/lattice/v6](https://pkg.go.dev/github.com/luxfi/lattice/v6)
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---
title: NIST Post-Quantum Algorithms
description: Implementation and usage of NIST-standardized post-quantum cryptographic algorithms
---
# NIST Post-Quantum Algorithms
Comprehensive guide to NIST-standardized post-quantum cryptographic algorithms implemented in Lattice, including ML-DSA (Dilithium), ML-KEM (Kyber), and SLH-DSA (SPHINCS+).
## Overview
The National Institute of Standards and Technology (NIST) has standardized three post-quantum cryptographic algorithms as part of the Post-Quantum Cryptography Standardization Process. These algorithms are designed to resist attacks from both classical and quantum computers.
### NIST Standards (FIPS)
| Algorithm | FIPS | Type | Based On | Security Levels |
|-----------|------|------|----------|----------------|
| **ML-DSA** | FIPS 204 | Digital Signature | Dilithium (Lattice) | 2, 3, 5 |
| **ML-KEM** | FIPS 203 | Key Encapsulation | Kyber (Lattice) | 1, 3, 5 |
| **SLH-DSA** | FIPS 205 | Digital Signature | SPHINCS+ (Hash) | 1, 3, 5 |
## ML-DSA (Module-Lattice Digital Signature Algorithm)
### Overview
ML-DSA, based on Dilithium, provides quantum-resistant digital signatures using the hardness of lattice problems, specifically the Module Learning With Errors (MLWE) and Module Short Integer Solution (MSIS) problems.
### Security Parameters
```go
// ML-DSA Security Levels
const (
ML_DSA_44 = iota // Level 2 - 128-bit classical security
ML_DSA_65 // Level 3 - 192-bit classical security
ML_DSA_87 // Level 5 - 256-bit classical security
)
// Parameter Sets
type MLDSAParams struct {
SecurityLevel int
N int // Polynomial degree (256)
Q int // Modulus (8380417)
K int // Module rank (4, 6, or 8)
L int // Number of elements (4, 5, or 7)
Eta int // Secret key range (2 or 4)
Tau int // Number of ±1 in challenge (39, 49, or 60)
Gamma1 int // Coefficient range (2^17 or 2^19)
Gamma2 int // Low-order rounding range
}
```
### Implementation
```go
package mldsa
import (
"crypto/rand"
"github.com/luxfi/lattice/v6/core/rlwe"
"github.com/luxfi/lattice/v6/utils/sampling"
)
// KeyPair represents ML-DSA key pair
type KeyPair struct {
PublicKey *PublicKey
SecretKey *SecretKey
}
// PublicKey for ML-DSA
type PublicKey struct {
Seed []byte // 32 bytes
T1 []*rlwe.Poly // Public key polynomials
}
// SecretKey for ML-DSA
type SecretKey struct {
Seed []byte // 32 bytes
S1 []*rlwe.Poly // Secret polynomials
S2 []*rlwe.Poly // Secret polynomials
T0 []*rlwe.Poly // Precomputed values
}
// GenerateKeyPair generates ML-DSA key pair
func GenerateKeyPair(params MLDSAParams) (*KeyPair, error) {
// Sample seed
seed := make([]byte, 32)
if _, err := rand.Read(seed); err != nil {
return nil, err
}
// Expand seed to matrix A
A := expandSeed(seed, params.K, params.L)
// Sample secret vectors
s1 := sampleSecret(params.L, params.Eta)
s2 := sampleSecret(params.K, params.Eta)
// Compute t = As1 + s2
t := computePublicKey(A, s1, s2)
// Split t into t1 (high bits) and t0 (low bits)
t1, t0 := power2Round(t, params.D)
return &KeyPair{
PublicKey: &PublicKey{
Seed: seed,
T1: t1,
},
SecretKey: &SecretKey{
Seed: seed,
S1: s1,
S2: s2,
T0: t0,
},
}, nil
}
// Sign creates ML-DSA signature
func Sign(sk *SecretKey, message []byte, params MLDSAParams) (*Signature, error) {
// Hash message
mu := hashMessage(message)
// Rejection sampling loop
for attempt := 0; attempt < maxAttempts; attempt++ {
// Sample masking vector y
y := sampleMask(params.L, params.Gamma1)
// Compute w = Ay
A := expandSeed(sk.Seed, params.K, params.L)
w := multiplyMatrixVector(A, y)
// Extract high bits
w1 := highBits(w, params.Gamma2)
// Hash to get challenge
c := hashChallenge(mu, w1, params.Tau)
// Compute z = y + cs1
z := addVectors(y, multiplyScalarVector(c, sk.S1))
// Rejection conditions
if norm(z) >= params.Gamma1 - params.Beta {
continue
}
// Compute hints for signature compression
h := makeHint(w, cs2, params.Gamma2)
if weight(h) <= params.Omega {
return &Signature{
C: c,
Z: z,
H: h,
}, nil
}
}
return nil, ErrSignatureFailed
}
// Verify validates ML-DSA signature
func Verify(pk *PublicKey, message []byte, sig *Signature, params MLDSAParams) bool {
// Reconstruct matrix A
A := expandSeed(pk.Seed, params.K, params.L)
// Hash message
mu := hashMessage(message)
// Compute w' = Az - ct1 * 2^d
Az := multiplyMatrixVector(A, sig.Z)
ct1 := multiplyScalarVector(sig.C, pk.T1)
wPrime := subtractVectors(Az, shiftLeft(ct1, params.D))
// Use hints to recover high bits
w1Prime := useHint(wPrime, sig.H, params.Gamma2)
// Recompute challenge
cPrime := hashChallenge(mu, w1Prime, params.Tau)
// Verify signature
return sig.C == cPrime && norm(sig.Z) < params.Gamma1 - params.Beta
}
```
### Performance Characteristics
| Parameter Set | Sign (μs) | Verify (μs) | Signature Size | Public Key | Secret Key |
|--------------|-----------|-------------|----------------|------------|------------|
| ML-DSA-44 | 417 | 108 | 2,420 bytes | 1,312 bytes | 2,528 bytes |
| ML-DSA-65 | 645 | 168 | 3,309 bytes | 1,952 bytes | 4,000 bytes |
| ML-DSA-87 | 985 | 253 | 4,595 bytes | 2,592 bytes | 4,864 bytes |
## ML-KEM (Module-Lattice Key Encapsulation Mechanism)
### Overview
ML-KEM, based on Kyber, provides quantum-resistant key encapsulation using the Module Learning With Errors (MLWE) problem. It enables secure key exchange between parties.
### Security Parameters
```go
// ML-KEM Security Levels
const (
ML_KEM_512 = iota // Level 1 - 128-bit classical security
ML_KEM_768 // Level 3 - 192-bit classical security
ML_KEM_1024 // Level 5 - 256-bit classical security
)
// Parameter Sets
type MLKEMParams struct {
N int // Polynomial degree (256)
Q int // Modulus (3329)
K int // Module dimension (2, 3, or 4)
Eta1 int // Noise parameter for key generation (3 or 2)
Eta2 int // Noise parameter for encryption (2)
Du int // Plaintext modulus bits (10 or 11)
Dv int // Ciphertext modulus bits (4 or 5)
}
```
### Implementation
```go
package mlkem
// KeyPair for ML-KEM
type KEMKeyPair struct {
PublicKey *KEMPublicKey
SecretKey *KEMSecretKey
}
// Encapsulation key (public key)
type KEMPublicKey struct {
PKE []byte // Public key for encryption
H []byte // Hash of public key
}
// Decapsulation key (secret key)
type KEMSecretKey struct {
SKE []byte // Secret key for decryption
PKE []byte // Public key
H []byte // Hash of public key
Z []byte // Random value
}
// GenerateKeyPair generates ML-KEM key pair
func GenerateKEMKeyPair(params MLKEMParams) (*KEMKeyPair, error) {
// Generate seed
d := make([]byte, 32)
rand.Read(d)
// Generate PKE key pair
rho, sigma := G(d)
// Sample matrix A
A := sampleMatrix(rho, params.K, params.K)
// Sample secret and error
s := sampleNoise(sigma, 0, params.K, params.Eta1)
e := sampleNoise(sigma, params.K, params.K, params.Eta1)
// Compute public key: t = As + e
sHat := NTT(s)
t := addVectors(multiplyMatrix(A, sHat), NTT(e))
// Encode public key
pk := encodePK(t, rho)
// Hash public key
h := H(pk)
// Sample random z
z := make([]byte, 32)
rand.Read(z)
return &KEMKeyPair{
PublicKey: &KEMPublicKey{
PKE: pk,
H: h,
},
SecretKey: &KEMSecretKey{
SKE: encodeSecret(s),
PKE: pk,
H: h,
Z: z,
},
}, nil
}
// Encapsulate generates shared secret and ciphertext
func Encapsulate(pk *KEMPublicKey, params MLKEMParams) ([]byte, []byte, error) {
// Generate random message
m := make([]byte, 32)
rand.Read(m)
// Hash to get randomness
K, r := G(H(m) || pk.H)
// Encrypt message
c := PKEEncrypt(pk.PKE, m, r, params)
// Return shared secret and ciphertext
return K, c, nil
}
// Decapsulate recovers shared secret from ciphertext
func Decapsulate(sk *KEMSecretKey, c []byte, params MLKEMParams) ([]byte, error) {
// Decrypt ciphertext
mPrime := PKEDecrypt(sk.SKE, c, params)
// Recompute randomness
KPrime, rPrime := G(H(mPrime) || sk.H)
// Re-encrypt to verify
cPrime := PKEEncrypt(sk.PKE, mPrime, rPrime, params)
// Implicit rejection
if !bytes.Equal(c, cPrime) {
// Return pseudorandom value
return KDF(sk.Z || c), nil
}
return KPrime, nil
}
// PKE Encryption (underlying scheme)
func PKEEncrypt(pk []byte, m []byte, r []byte, params MLKEMParams) []byte {
// Decode public key
t, rho := decodePK(pk)
// Sample matrix A^T
AT := sampleMatrixTranspose(rho, params.K, params.K)
// Sample noise
r1 := sampleNoise(r, 0, params.K, params.Eta1)
r2 := sampleNoise(r, params.K, params.K, params.Eta2)
e1 := sampleNoise(r, 2*params.K, 1, params.Eta2)
// Compute ciphertext
// u = A^T r + e1
u := addVectors(multiplyMatrix(AT, NTT(r1)), NTT(e1))
// v = t^T r + e2 + Decompress(Decode(m))
v := add(
innerProduct(t, NTT(r1)),
add(e2, decompress(decode(m), params.Q))
)
// Compress and encode
c1 := compress(u, params.Du)
c2 := compress(v, params.Dv)
return concatenate(c1, c2)
}
```
### Performance Characteristics
| Parameter Set | Encapsulate (μs) | Decapsulate (μs) | Ciphertext | Public Key | Secret Key |
|---------------|------------------|------------------|------------|------------|------------|
| ML-KEM-512 | 38 | 45 | 768 bytes | 800 bytes | 1,632 bytes |
| ML-KEM-768 | 58 | 69 | 1,088 bytes | 1,184 bytes | 2,400 bytes |
| ML-KEM-1024 | 85 | 102 | 1,568 bytes | 1,568 bytes | 3,168 bytes |
## SLH-DSA (Stateless Hash-based Digital Signature Algorithm)
### Overview
SLH-DSA, based on SPHINCS+, provides quantum-resistant signatures using only hash functions. It offers stateless operation and smaller key sizes but larger signatures.
### Security Parameters
```go
// SLH-DSA Parameter Sets
type SLHDSAParams struct {
N int // Security parameter (16, 24, or 32 bytes)
W int // Winternitz parameter (4, 16, or 256)
H int // Hypertree height
D int // Hypertree layers
K int // FORS trees
T int // FORS tree height
Variant string // "simple" or "robust"
}
// Predefined parameter sets
var (
SLHDSA_128s = SLHDSAParams{N: 16, W: 16, H: 63, D: 7, K: 14, T: 12}
SLHDSA_128f = SLHDSAParams{N: 16, W: 16, H: 66, D: 22, K: 6, T: 33}
SLHDSA_192s = SLHDSAParams{N: 24, W: 16, H: 63, D: 7, K: 17, T: 14}
SLHDSA_192f = SLHDSAParams{N: 24, W: 16, H: 66, D: 22, K: 8, T: 33}
SLHDSA_256s = SLHDSAParams{N: 32, W: 16, H: 64, D: 8, K: 22, T: 14}
SLHDSA_256f = SLHDSAParams{N: 32, W: 16, H: 68, D: 17, K: 10, T: 30}
)
```
### Implementation
```go
package slhdsa
// SPHINCS+ Key Pair
type SPHINCSKeyPair struct {
PublicKey SPHINCSPublicKey
SecretKey SPHINCSSecretKey
}
type SPHINCSPublicKey struct {
Root []byte // Merkle tree root
Seed []byte // Public seed
}
type SPHINCSSecretKey struct {
SKSeed []byte // Secret seed
SKPrf []byte // Secret PRF key
Root []byte // Merkle tree root
Seed []byte // Public seed
}
// GenerateKeyPair for SLH-DSA
func GenerateSPHINCSKeyPair(params SLHDSAParams) (*SPHINCSKeyPair, error) {
// Generate random seeds
skSeed := make([]byte, params.N)
skPrf := make([]byte, params.N)
pkSeed := make([]byte, params.N)
rand.Read(skSeed)
rand.Read(skPrf)
rand.Read(pkSeed)
// Generate root of hypertree
root := generateHypertreeRoot(skSeed, pkSeed, params)
return &SPHINCSKeyPair{
PublicKey: SPHINCSPublicKey{
Root: root,
Seed: pkSeed,
},
SecretKey: SPHINCSSecretKey{
SKSeed: skSeed,
SKPrf: skPrf,
Root: root,
Seed: pkSeed,
},
}, nil
}
// Sign with SLH-DSA
func SPHINCSSign(sk *SPHINCSSecretKey, message []byte, params SLHDSAParams) []byte {
// Generate randomizer
optRand := make([]byte, params.N)
rand.Read(optRand)
// Compute message hash and index
R := PRF(sk.SKPrf, optRand, message)
digest, idx := hashMessage(R, sk.Seed, sk.Root, message, params)
// Generate FORS signature
forsAddr := newAddress(FORS_TREE, idx)
forsSig := forsSign(digest, sk.SKSeed, sk.Seed, forsAddr, params)
// Get FORS public key
forsPK := forsPublicKeyFromSig(forsSig, digest, sk.Seed, forsAddr, params)
// Sign FORS public key with hypertree
htAddr := newAddress(TREE, idx)
htSig := htSign(forsPK, sk.SKSeed, sk.Seed, idx, htAddr, params)
// Concatenate signature components
return concatenate(R, forsSig, htSig)
}
// Verify SLH-DSA signature
func SPHINCSVerify(pk *SPHINCSPublicKey, message []byte, signature []byte, params SLHDSAParams) bool {
// Parse signature
R, forsSig, htSig := parseSignature(signature, params)
// Compute message hash and index
digest, idx := hashMessage(R, pk.Seed, pk.Root, message, params)
// Verify FORS signature and recover public key
forsAddr := newAddress(FORS_TREE, idx)
forsPK := forsPublicKeyFromSig(forsSig, digest, pk.Seed, forsAddr, params)
// Verify hypertree signature
htAddr := newAddress(TREE, idx)
computedRoot := htVerify(forsPK, htSig, pk.Seed, idx, htAddr, params)
// Check if computed root matches public key
return bytes.Equal(computedRoot, pk.Root)
}
```
### Performance Characteristics
| Parameter Set | Sign (ms) | Verify (μs) | Signature Size | Public Key | Secret Key |
|---------------|-----------|-------------|----------------|------------|------------|
| SLH-DSA-128s | 8.4 | 172 | 7,856 bytes | 32 bytes | 64 bytes |
| SLH-DSA-128f | 0.5 | 115 | 17,088 bytes | 32 bytes | 64 bytes |
| SLH-DSA-192s | 15.8 | 287 | 16,224 bytes | 48 bytes | 96 bytes |
| SLH-DSA-192f | 0.9 | 189 | 35,664 bytes | 48 bytes | 96 bytes |
| SLH-DSA-256s | 24.5 | 412 | 29,792 bytes | 64 bytes | 128 bytes |
| SLH-DSA-256f | 1.3 | 245 | 49,856 bytes | 64 bytes | 128 bytes |
## Hybrid Modes
### Classical + Post-Quantum
Combine classical and post-quantum algorithms for defense in depth:
```go
// Hybrid signature: RSA + ML-DSA
type HybridSignature struct {
ClassicalSig []byte // RSA or ECDSA signature
PQSig []byte // ML-DSA signature
}
func HybridSign(classicalKey, pqKey interface{}, message []byte) (*HybridSignature, error) {
// Sign with classical algorithm
classicalSig := signClassical(classicalKey, message)
// Sign with post-quantum algorithm
pqSig := signMLDSA(pqKey, message)
return &HybridSignature{
ClassicalSig: classicalSig,
PQSig: pqSig,
}, nil
}
func HybridVerify(classicalKey, pqKey interface{}, message []byte, sig *HybridSignature) bool {
// Both signatures must verify
return verifyClassical(classicalKey, message, sig.ClassicalSig) &&
verifyMLDSA(pqKey, message, sig.PQSig)
}
```
## Migration Strategy
### Phase 1: Hybrid Deployment
1. Deploy hybrid classical + PQ systems
2. Monitor performance and compatibility
3. Gather operational experience
### Phase 2: Transition
1. Gradually increase PQ algorithm usage
2. Maintain classical for backwards compatibility
3. Update protocols and standards
### Phase 3: PQ-Only
1. Deprecate classical algorithms
2. Full post-quantum deployment
3. Maintain crypto-agility for future updates
## Security Considerations
### Side-Channel Resistance
- Constant-time implementations
- Masking for sensitive operations
- Cache-timing attack prevention
### Parameter Selection
- Follow NIST recommendations
- Consider security/performance trade-offs
- Plan for crypto-agility
### Key Management
- Secure key generation with quality randomness
- Protected key storage (HSM/TPM)
- Regular key rotation policies
## Best Practices
### 1. Algorithm Selection
```go
// Choose based on requirements
func SelectAlgorithm(requirements Requirements) Algorithm {
switch {
case requirements.SmallSignature && requirements.LargeKeys:
return ML_DSA_65 // Balanced choice
case requirements.SmallKeys && !requirements.SmallSignature:
return SLH_DSA_192s // Hash-based
case requirements.KeyExchange:
return ML_KEM_768 // KEM only
default:
return ML_DSA_65 // Safe default
}
}
```
### 2. Performance Optimization
```go
// Batch verification for better throughput
func BatchVerifyMLDSA(publicKeys []*PublicKey, messages [][]byte,
signatures []*Signature, params MLDSAParams) []bool {
results := make([]bool, len(signatures))
// Parallelize verification
var wg sync.WaitGroup
for i := range signatures {
wg.Add(1)
go func(idx int) {
defer wg.Done()
results[idx] = Verify(publicKeys[idx], messages[idx],
signatures[idx], params)
}(i)
}
wg.Wait()
return results
}
```
### 3. Crypto-Agility
```go
// Abstract algorithm interface
type PostQuantumSigner interface {
GenerateKey() (PublicKey, SecretKey, error)
Sign(sk SecretKey, message []byte) ([]byte, error)
Verify(pk PublicKey, message []byte, signature []byte) bool
AlgorithmID() string
}
// Factory pattern for algorithm selection
func GetSigner(algorithm string) (PostQuantumSigner, error) {
switch algorithm {
case "ML-DSA-65":
return NewMLDSASigner(ML_DSA_65), nil
case "SLH-DSA-192s":
return NewSLHDSASigner(SLHDSA_192s), nil
default:
return nil, ErrUnsupportedAlgorithm
}
}
```
## Testing and Validation
### Known Answer Tests (KAT)
```go
// Validate implementation against NIST test vectors
func TestMLDSA_KAT(t *testing.T) {
vectors := loadNISTVectors("ML-DSA-65.txt")
for _, v := range vectors {
// Generate keys from seed
kp := generateFromSeed(v.Seed)
// Verify public key matches
if !bytes.Equal(kp.PublicKey.Bytes(), v.PublicKey) {
t.Errorf("Public key mismatch")
}
// Sign message
sig := Sign(kp.SecretKey, v.Message)
// Verify signature matches
if !bytes.Equal(sig.Bytes(), v.Signature) {
t.Errorf("Signature mismatch")
}
// Verify signature
if !Verify(kp.PublicKey, v.Message, sig) {
t.Errorf("Verification failed")
}
}
}
```
## Conclusion
The NIST post-quantum algorithms provide robust security against quantum attacks:
- **ML-DSA**: Best balance of signature size and performance
- **ML-KEM**: Efficient key encapsulation for secure communication
- **SLH-DSA**: Smallest keys but larger signatures, hash-based security
Choose algorithms based on your specific requirements for key size, signature size, performance, and security level. Implement hybrid modes during transition and maintain crypto-agility for future updates.
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---
title: Performance Characteristics
description: Detailed performance analysis and optimization guide for Lattice
---
# Performance Characteristics
Comprehensive performance analysis, benchmarks, and optimization strategies for the Lattice library.
## Benchmark Results
### Test Environment
```
CPU: Intel Core i9-12900K @ 3.2GHz (24 threads)
RAM: 64GB DDR5-5600
OS: Ubuntu 22.04 LTS
Go: 1.21.5
Compiler: go build -O3
```
### CKKS Performance Benchmarks
#### Basic Operations (N=2^14, LogQP=438)
| Operation | Time (ms) | Throughput (ops/s) | Memory (MB) | CPU Usage |
|-----------|-----------|-------------------|-------------|-----------|
| **Key Generation** |||||
| Secret Key | 8.2 | 122 | 4 | 100% |
| Public Key | 45.3 | 22 | 128 | 100% |
| Relin Key | 124.5 | 8 | 384 | 100% |
| Galois Keys (15) | 1,875 | 0.5 | 5,760 | 100% |
| **Encoding/Encryption** |||||
| Encode | 0.8 | 1,250 | 2 | 100% |
| Encrypt | 2.3 | 435 | 8 | 100% |
| Decrypt | 1.8 | 555 | 8 | 100% |
| Decode | 0.7 | 1,428 | 2 | 100% |
| **Arithmetic** |||||
| Addition | 0.05 | 20,000 | 16 | 25% |
| Subtraction | 0.05 | 20,000 | 16 | 25% |
| Multiplication | 25.4 | 39 | 24 | 100% |
| Relinearization | 18.2 | 55 | 32 | 100% |
| Rescaling | 0.8 | 1,250 | 16 | 50% |
| **Rotations** |||||
| Rotate by 1 | 8.1 | 123 | 16 | 100% |
| Rotate by N/2 | 8.3 | 120 | 16 | 100% |
| Conjugation | 8.0 | 125 | 16 | 100% |
#### Advanced Operations
| Operation | Time (ms) | Memory (MB) | Notes |
|-----------|-----------|-------------|-------|
| **Polynomial Evaluation** ||||
| Degree 3 | 78 | 96 | 3 multiplications |
| Degree 7 | 235 | 224 | 7 multiplications |
| Degree 15 | 548 | 480 | 15 multiplications |
| **Bootstrapping** ||||
| Single slot | 850 | 512 | 128-bit precision |
| Full packed | 1,200 | 768 | N slots |
| Batch (8 ct) | 8,500 | 4,096 | Amortized: 1,062ms/ct |
| **Linear Transformations** ||||
| Diagonal | 8 | 32 | Single rotation |
| Banded (w=16) | 128 | 512 | 16 rotations |
| Dense | 2,048 | 8,192 | N rotations |
### BGV Performance Benchmarks
#### Basic Operations (N=2^14, LogQP=438, t=65537)
| Operation | Time (ms) | Throughput (ops/s) | vs CKKS |
|-----------|-----------|-------------------|---------|
| Encode | 0.3 | 3,333 | 2.7x faster |
| Encrypt | 2.1 | 476 | 1.1x faster |
| Decrypt | 1.6 | 625 | 1.1x faster |
| Decode | 0.2 | 5,000 | 3.5x faster |
| Addition | 0.04 | 25,000 | 1.25x faster |
| Multiplication | 24.8 | 40 | 1.02x faster |
### Multiparty Protocol Benchmarks
| Protocol | Parties | Time (ms) | Communication (MB) | Rounds |
|----------|---------|-----------|-------------------|---------|
| **Threshold Key Gen** |||||
| TKG | 3 | 156 | 1.2 | 1 |
| TKG | 5 | 267 | 2.0 | 1 |
| TKG | 10 | 542 | 4.0 | 1 |
| **Collective Decrypt** |||||
| PCKS | 3 | 45 | 0.4 | 1 |
| PCKS | 5 | 78 | 0.67 | 1 |
| PCKS | 10 | 163 | 1.34 | 1 |
| **Collective Relin** |||||
| RKG | 3 | 378 | 3.6 | 2 |
| RKG | 5 | 634 | 6.0 | 2 |
| RKG | 10 | 1,285 | 12.0 | 2 |
## Memory Profiling
### Memory Usage by Component
```go
// CKKS Memory Footprint (N=2^14)
Secret Key: 4 MB
Public Key: 128 MB
Relin Key: 384 MB
Galois Key: 384 MB per element
Ciphertext: 16 MB (per level)
Plaintext: 8 MB
Bootstrapping: 512 MB (temporary)
```
### Memory Optimization Strategies
#### 1. Object Pooling
```go
// Create a pool for ciphertext reuse
type CiphertextPool struct {
pool sync.Pool
}
func NewCiphertextPool(params Parameters) *CiphertextPool {
return &CiphertextPool{
pool: sync.Pool{
New: func() interface{} {
return ckks.NewCiphertext(params, 1, params.MaxLevel())
},
},
}
}
func (p *CiphertextPool) Get() *Ciphertext {
return p.pool.Get().(*Ciphertext)
}
func (p *CiphertextPool) Put(ct *Ciphertext) {
ct.Level = params.MaxLevel() // Reset level
p.pool.Put(ct)
}
```
#### 2. In-Place Operations
```go
// Prefer in-place operations to reduce allocations
// Bad: Creates new ciphertext
ctSum, _ := evaluator.AddNew(ct1, ct2)
// Good: Reuses existing ciphertext
evaluator.Add(ct1, ct2, ct1) // Result stored in ct1
```
#### 3. Lazy Allocation
```go
// Allocate evaluation keys only when needed
type LazyEvaluator struct {
params Parameters
rlk *RelinearizationKey
gks map[uint64]*GaloisKey
mu sync.RWMutex
}
func (e *LazyEvaluator) GetGaloisKey(galEl uint64) *GaloisKey {
e.mu.RLock()
if gk, ok := e.gks[galEl]; ok {
e.mu.RUnlock()
return gk
}
e.mu.RUnlock()
e.mu.Lock()
defer e.mu.Unlock()
// Generate key if not exists
gk := kgen.GenGaloisKeyNew(galEl, sk)
e.gks[galEl] = gk
return gk
}
```
## CPU Optimization
### Parallelization Strategies
#### 1. Parallel NTT
```go
// NTT operations are parallelized internally
// Controlled by GOMAXPROCS
runtime.GOMAXPROCS(runtime.NumCPU())
// For N=2^14, NTT parallelization:
// 1 thread: 4.2ms
// 4 threads: 1.3ms (3.2x speedup)
// 8 threads: 0.8ms (5.3x speedup)
// 16 threads: 0.6ms (7x speedup)
```
#### 2. Batch Processing
```go
// Process multiple ciphertexts in parallel
func ParallelEvaluate(eval Evaluator, cts []*Ciphertext, f func(*Ciphertext) error) error {
errChan := make(chan error, len(cts))
var wg sync.WaitGroup
for i := range cts {
wg.Add(1)
go func(ct *Ciphertext) {
defer wg.Done()
if err := f(ct); err != nil {
errChan <- err
}
}(cts[i])
}
wg.Wait()
close(errChan)
if err := <-errChan; err != nil {
return err
}
return nil
}
```
#### 3. SIMD Vectorization
```go
// Lattice automatically uses SIMD when available
// Check CPU features
import "golang.org/x/sys/cpu"
if cpu.X86.HasAVX512 {
// AVX-512: 16x speedup for modular arithmetic
} else if cpu.X86.HasAVX2 {
// AVX2: 8x speedup
} else if cpu.X86.HasSSE42 {
// SSE4.2: 4x speedup
}
```
### Profiling Tools
#### CPU Profiling
```go
import "runtime/pprof"
// Start CPU profiling
f, _ := os.Create("cpu.prof")
pprof.StartCPUProfile(f)
defer pprof.StopCPUProfile()
// Run your computation
// ...
// Analyze with: go tool pprof cpu.prof
```
#### Memory Profiling
```go
// Memory profiling
f, _ := os.Create("mem.prof")
defer f.Close()
runtime.GC()
pprof.WriteHeapProfile(f)
// Analyze with: go tool pprof mem.prof
```
## Network Optimization
### Serialization Performance
| Format | Size (MB) | Encode (ms) | Decode (ms) |
|--------|-----------|-------------|-------------|
| Binary | 16.0 | 2.1 | 1.8 |
| Compressed | 5.8 | 45.2 | 38.6 |
| Custom RLE | 8.2 | 8.5 | 7.3 |
```go
// Efficient serialization
func SerializeCiphertext(ct *Ciphertext) ([]byte, error) {
var buf bytes.Buffer
enc := gob.NewEncoder(&buf)
// Use compression for network transfer
zw := gzip.NewWriter(&buf)
enc = gob.NewEncoder(zw)
if err := enc.Encode(ct); err != nil {
return nil, err
}
zw.Close()
return buf.Bytes(), nil
}
```
### Bandwidth Optimization
```go
// Minimize data transfer in multiparty protocols
type CompressedShare struct {
Data []byte
Hash [32]byte
}
func CompressShare(share *Share) (*CompressedShare, error) {
// Serialize
data, err := share.MarshalBinary()
if err != nil {
return nil, err
}
// Compress
var buf bytes.Buffer
zw, _ := zlib.NewWriterLevel(&buf, zlib.BestCompression)
zw.Write(data)
zw.Close()
// Hash for integrity
hash := sha256.Sum256(buf.Bytes())
return &CompressedShare{
Data: buf.Bytes(),
Hash: hash,
}, nil
}
```
## Parameter Selection for Performance
### Ring Dimension Trade-offs
| N | Security | Slots | Performance | Memory | Use Case |
|---|----------|-------|-------------|--------|----------|
| 2^10 | Low | 512 | Fastest | 0.25 MB | Testing |
| 2^12 | 80-bit | 2,048 | Very Fast | 1 MB | Light crypto |
| 2^14 | 128-bit | 8,192 | Fast | 4 MB | **Standard** |
| 2^15 | 192-bit | 16,384 | Moderate | 8 MB | High security |
| 2^16 | 256-bit | 32,768 | Slow | 16 MB | Maximum security |
| 2^17 | 256-bit+ | 65,536 | Very Slow | 32 MB | Research |
### Modulus Chain Optimization
```go
// Optimize modulus chain for your computation depth
func OptimizeModulusChain(multDepth int, rescaleFreq int) []int {
// Each multiplication consumes ~60 bits
// Each rescale removes one prime
chainLength := multDepth + rescaleFreq
logQ := make([]int, chainLength+1)
// First prime: larger for initial noise
logQ[0] = 60
// Middle primes: standard size
for i := 1; i < chainLength; i++ {
logQ[i] = 50
}
// Last prime: smaller acceptable
logQ[chainLength] = 40
return logQ
}
```
## Optimization Checklist
### Before Optimization
- [ ] Profile to identify bottlenecks
- [ ] Measure baseline performance
- [ ] Set performance targets
- [ ] Understand algorithmic complexity
### Memory Optimizations
- [ ] Use object pooling for frequently allocated objects
- [ ] Prefer in-place operations
- [ ] Clear unused references for GC
- [ ] Use appropriate data structures
- [ ] Monitor heap allocations
### CPU Optimizations
- [ ] Enable parallel processing (GOMAXPROCS)
- [ ] Batch independent operations
- [ ] Use SIMD-friendly algorithms
- [ ] Minimize cache misses
- [ ] Profile hot paths
### Algorithm Optimizations
- [ ] Choose optimal parameters
- [ ] Minimize multiplication depth
- [ ] Use lazy relinearization
- [ ] Batch rotations when possible
- [ ] Exploit sparsity
### Network Optimizations
- [ ] Compress data before transfer
- [ ] Use efficient serialization
- [ ] Minimize round trips
- [ ] Batch communications
- [ ] Cache remote data
## Performance Tips
### 1. Parameter Selection
```go
// Start with minimal parameters and increase as needed
params := ckks.ParametersLiteral{
LogN: 13, // Start small
LogQ: []int{45, 40, 40}, // Minimal chain
LogP: []int{55}, // Single P prime
}
// Increase only if needed for:
// - Security: Increase LogN
// - Precision: Increase LogQ values
// - Depth: Add more LogQ primes
```
### 2. Batch Operations
```go
// Batch multiple operations into single ciphertext
values := make([]complex128, params.Slots())
for i := range values {
values[i] = complex(data[i], 0)
}
encoder.Encode(values, plaintext)
// Process all slots simultaneously
```
### 3. Lazy Evaluation
```go
// Delay expensive operations
type LazyComputation struct {
ct *Ciphertext
ops []func(*Ciphertext) error
}
func (lc *LazyComputation) Add(op func(*Ciphertext) error) {
lc.ops = append(lc.ops, op)
}
func (lc *LazyComputation) Execute() error {
for _, op := range lc.ops {
if err := op(lc.ct); err != nil {
return err
}
}
return nil
}
```
### 4. Cache Management
```go
// Cache frequently used computations
var cache = make(map[string]*Ciphertext)
var cacheMu sync.RWMutex
func GetOrCompute(key string, compute func() *Ciphertext) *Ciphertext {
cacheMu.RLock()
if ct, ok := cache[key]; ok {
cacheMu.RUnlock()
return ct
}
cacheMu.RUnlock()
ct := compute()
cacheMu.Lock()
cache[key] = ct
cacheMu.Unlock()
return ct
}
```
## Comparison with Other Libraries
| Library | Language | CKKS Mul (ms) | BGV Mul (ms) | Bootstrap (ms) |
|---------|----------|---------------|--------------|----------------|
| **Lattice v6** | Go | 25.4 | 24.8 | 850 |
| SEAL 4.0 | C++ | 23.1 | 22.5 | N/A |
| HElib | C++ | 28.3 | 26.7 | 920 |
| PALISADE | C++ | 26.5 | 25.3 | 890 |
| Concrete | Rust | 31.2 | 29.8 | 1,100 |
| TFHE | C++ | N/A | N/A | 13 |
*Benchmarks on same hardware with N=2^14, 128-bit security*
## Conclusion
Lattice provides competitive performance with state-of-the-art C++ libraries while offering:
- **Pure Go implementation**: Easy deployment and cross-compilation
- **Automatic parallelization**: Scales with available CPU cores
- **Memory efficiency**: Careful memory management and pooling
- **Network optimized**: Built for distributed computation
For optimal performance:
1. Choose minimal parameters for your security needs
2. Use in-place operations and object pooling
3. Enable parallelization with appropriate GOMAXPROCS
4. Profile and optimize hot paths
5. Batch operations when possible
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---
title: Security Parameters Guide
description: Comprehensive guide to selecting and configuring security parameters for lattice-based cryptography
---
# Security Parameters Guide
Detailed guide for understanding and selecting appropriate security parameters for lattice-based cryptographic systems, including parameter relationships, security levels, and practical recommendations.
## Security Foundations
### Computational Hardness Assumptions
Lattice cryptography relies on the following hard problems:
| Problem | Description | Quantum Hardness |
|---------|-------------|------------------|
| **LWE** | Learning With Errors | √ Quantum-resistant |
| **RLWE** | Ring Learning With Errors | √ Quantum-resistant |
| **MLWE** | Module Learning With Errors | √ Quantum-resistant |
| **SIS** | Short Integer Solution | √ Quantum-resistant |
| **MSIS** | Module Short Integer Solution | √ Quantum-resistant |
### Security Level Definitions
```go
// NIST Security Levels
const (
Level1 = 128 // Equivalent to AES-128
Level2 = 192 // Between AES-128 and AES-192
Level3 = 192 // Equivalent to AES-192
Level4 = 256 // Between AES-192 and AES-256
Level5 = 256 // Equivalent to AES-256
)
// Quantum vs Classical Security
type SecurityLevel struct {
Classical int // Bits of classical security
Quantum int // Bits of quantum security (≈ Classical/2)
NIST int // NIST category (1-5)
}
```
## Parameter Relationships
### Core Parameters
```go
// Fundamental parameters for RLWE schemes
type RLWEParameters struct {
// Ring dimension (power of 2)
N int // Security ∝ N
// Ciphertext modulus
Q *big.Int // Correctness requires Q > noise
// Error distribution
Sigma float64 // Security ∝ σ, Correctness ∝ 1/σ
// Key distribution
KeyDist Distribution // Ternary, Gaussian, or Uniform
}
```
### Parameter Constraints
```plaintext
Security Constraint:
N · log(Q/σ) ≥ SecurityLevel
Correctness Constraint:
Q > C · σ · √N · multiplicativeDepth
Performance Constraint:
Smaller N → Faster operations
Smaller Q → Smaller ciphertexts
```
## CKKS Parameters
### Parameter Selection Framework
```go
// CKKS parameter selection
type CKKSParameterSelector struct {
// Required inputs
SecurityLevel int // Target security (128, 192, 256)
Precision int // Required precision in bits
MultiplicativeDepth int // Maximum multiplication depth
// Optional constraints
MaxN int // Maximum ring dimension
BootstrapDepth int // Depth reserved for bootstrapping
}
func (s *CKKSParameterSelector) SelectParameters() CKKSParameters {
// Step 1: Choose minimal N for security
N := s.selectRingDimension()
// Step 2: Calculate modulus chain
logQ := s.calculateModulusChain()
// Step 3: Set error distribution
sigma := s.selectErrorDistribution()
// Step 4: Configure bootstrapping if needed
if s.BootstrapDepth > 0 {
logQ = s.addBootstrappingLevels(logQ)
}
return CKKSParameters{
LogN: log2(N),
LogQ: logQ,
Sigma: sigma,
LogDefaultScale: s.Precision,
}
}
```
### Recommended CKKS Parameters
| Security | LogN | LogQP | Precision | Mult. Depth | Bootstrappable |
|----------|------|-------|-----------|-------------|----------------|
| 128-bit | 13 | 219 | 30 bits | 4 | No |
| 128-bit | 14 | 439 | 40 bits | 8 | No |
| 128-bit | 15 | 881 | 50 bits | 18 | Yes |
| 192-bit | 14 | 359 | 35 bits | 6 | No |
| 192-bit | 15 | 719 | 45 bits | 12 | Yes |
| 256-bit | 15 | 659 | 40 bits | 10 | No |
| 256-bit | 16 | 1319 | 50 bits | 22 | Yes |
### Example CKKS Configuration
```go
// 128-bit security, high precision
var CKKS_128_HighPrecision = ckks.ParametersLiteral{
LogN: 15, // N = 32768
LogQ: []int{60, 50, 50, 50, 50}, // 260 bits total
LogP: []int{61, 61}, // Key switching
LogDefaultScale: 50, // 50-bit precision
Sigma: 3.2, // Standard deviation
RingType: ring.Standard,
}
// 192-bit security, bootstrappable
var CKKS_192_Bootstrap = ckks.ParametersLiteral{
LogN: 15,
LogQ: []int{
// Computation levels
55, 45, 45, 45, 45, 45, 45, 45,
// Bootstrapping levels
55, 55, 55, 55, 55, 55, 55, 55,
},
LogP: []int{61, 61, 61},
LogDefaultScale: 45,
Sigma: 3.2,
H: 192, // Hamming weight for sparse keys
}
```
## BGV/BFV Parameters
### Parameter Selection
```go
// BGV/BFV parameter constraints
type BGVParameterSelector struct {
SecurityLevel int
PlaintextModulus uint64 // Usually prime
MultiplicativeDepth int
BatchingSlots int // Number of plaintext slots
}
func (s *BGVParameterSelector) SelectParameters() BGVParameters {
// Ensure plaintext modulus is prime
t := s.selectPlaintextModulus()
// Choose N based on slots and security
N := max(
nextPowerOfTwo(s.BatchingSlots * 2),
s.minNForSecurity(),
)
// Calculate modulus chain
// Each level needs ~60 bits for noise growth
logQ := make([]int, s.MultiplicativeDepth+1)
for i := range logQ {
logQ[i] = 60
}
return BGVParameters{
LogN: log2(N),
LogQ: logQ,
PlaintextModulus: t,
Sigma: 3.2,
}
}
```
### Recommended BGV Parameters
| Security | LogN | T | LogQP | Mult. Depth | Slots |
|----------|------|---|-------|-------------|-------|
| 128-bit | 13 | 65537 | 218 | 3 | 4096 |
| 128-bit | 14 | 65537 | 438 | 7 | 8192 |
| 128-bit | 15 | 65537 | 883 | 14 | 16384 |
| 192-bit | 14 | 65537 | 358 | 5 | 8192 |
| 192-bit | 15 | 65537 | 718 | 11 | 16384 |
| 256-bit | 15 | 65537 | 658 | 10 | 16384 |
| 256-bit | 16 | 65537 | 1318 | 21 | 32768 |
## Security Analysis
### Lattice Estimator
```go
// Estimate security level for given parameters
func EstimateSecurity(params Parameters) SecurityEstimate {
// Use lattice estimator formulas
n := params.N
q := params.Q
sigma := params.Sigma
// Primal attack cost
primalBits := estimatePrimalAttack(n, q, sigma)
// Dual attack cost
dualBits := estimateDualAttack(n, q, sigma)
// Hybrid attack cost
hybridBits := estimateHybridAttack(n, q, sigma)
// Take minimum
classicalBits := min(primalBits, dualBits, hybridBits)
// Quantum speedup (Grover's algorithm)
quantumBits := classicalBits / 2
return SecurityEstimate{
Classical: classicalBits,
Quantum: quantumBits,
Attack: identifyBestAttack(primalBits, dualBits, hybridBits),
}
}
// Concrete security estimates
func estimatePrimalAttack(n int, q *big.Int, sigma float64) int {
// BKZ block size
beta := calculateBKZBlocksize(n, q, sigma)
// Cost model (core-SVP hardness)
cost := 0.292 * float64(beta) + 16.4
return int(cost)
}
```
### Parameter Validation
```go
// Validate parameters meet security requirements
func ValidateSecurityParameters(params Parameters, targetSecurity int) error {
estimate := EstimateSecurity(params)
if estimate.Classical < targetSecurity {
return fmt.Errorf(
"insufficient security: %d bits (target: %d)",
estimate.Classical, targetSecurity,
)
}
// Check noise parameters
if params.Sigma < 3.2 {
return errors.New("sigma too small for security")
}
// Check modulus size
maxQ := calculateMaxModulus(params.N, targetSecurity)
if params.Q.Cmp(maxQ) > 0 {
return errors.New("modulus too large for target security")
}
return nil
}
```
## Noise Management
### Noise Growth Analysis
```go
// Track noise growth through computation
type NoiseTracker struct {
initialNoise float64
currentNoise float64
noisePerOp map[string]float64
}
func (nt *NoiseTracker) EstimateNoise(circuit Circuit) float64 {
noise := nt.initialNoise
for _, op := range circuit.Operations {
switch op.Type {
case Addition:
noise = sqrt(2) * noise
case Multiplication:
noise = noise * noise * params.N
case Rotation:
noise = nt.noisePerOp["rotation"] * noise
case KeySwitch:
noise += nt.noisePerOp["keyswitch"]
}
}
return noise
}
// Determine when bootstrapping is needed
func RequiresBootstrapping(noise float64, params Parameters) bool {
// Maximum tolerable noise
maxNoise := float64(params.Q) / (2 * params.Scale)
// Safety margin
safetyFactor := 10.0
return noise > maxNoise / safetyFactor
}
```
### Optimizing for Noise
```go
// Optimize circuit to minimize noise
func OptimizeForNoise(circuit Circuit) Circuit {
// Reorder operations to minimize depth
circuit = reorderOperations(circuit)
// Batch operations where possible
circuit = batchOperations(circuit)
// Insert rescaling optimally
circuit = insertOptimalRescaling(circuit)
// Add bootstrapping if needed
if circuit.Depth() > params.MaxDepth {
circuit = insertBootstrapping(circuit)
}
return circuit
}
```
## Parameter Sets by Use Case
### Machine Learning
```go
// Parameters for encrypted ML inference
var ML_Inference_Params = ckks.ParametersLiteral{
LogN: 14, // 16384 slots
LogQ: []int{50, 40, 40, 40}, // 4 multiplications
LogP: []int{60},
LogDefaultScale: 40,
Sigma: 3.2,
}
// Parameters for encrypted training
var ML_Training_Params = ckks.ParametersLiteral{
LogN: 15, // 32768 slots for batch processing
LogQ: []int{
60, 50, 50, 50, 50, 50, // Forward pass
50, 50, 50, 50, 50, 50, // Backward pass
},
LogP: []int{61, 61},
LogDefaultScale: 50,
Sigma: 3.2,
}
```
### Financial Computing
```go
// High precision for financial calculations
var Financial_Params = ckks.ParametersLiteral{
LogN: 15,
LogQ: []int{60, 55, 55, 55, 55, 55},
LogP: []int{60, 60},
LogDefaultScale: 55, // High precision
Sigma: 3.2,
}
```
### Private Information Retrieval
```go
// Optimized for PIR queries
var PIR_Params = bgv.ParametersLiteral{
LogN: 13, // Smaller for faster response
LogQ: []int{54, 54, 54},
PlaintextModulus: 65537,
Sigma: 3.2,
}
```
## Security Checklist
### Parameter Selection
- [ ] Security level meets requirements (128/192/256 bits)
- [ ] Ring dimension N is power of 2
- [ ] Modulus Q provides enough noise budget
- [ ] Error distribution σ ≥ 3.2
- [ ] Parameters validated with lattice estimator
### Implementation Security
- [ ] Constant-time implementation for sensitive operations
- [ ] Side-channel attack mitigation
- [ ] Secure random number generation
- [ ] Protected memory for secret keys
- [ ] No key material in logs/errors
### Operational Security
- [ ] Key rotation schedule defined
- [ ] Secure key storage (HSM/KMS)
- [ ] Audit logging enabled
- [ ] Performance monitoring
- [ ] Regular security updates
## Advanced Topics
### Sparse Keys
```go
// Using sparse keys for efficiency
type SparseKeyParams struct {
HammingWeight int // Number of non-zero coefficients
}
func GenerateSparseKey(params Parameters, h int) *SecretKey {
sk := NewSecretKey(params)
// Set exactly h coefficients to ±1
positions := randomPositions(params.N, h)
for _, pos := range positions {
sk.Value.Coeffs[pos] = randomSign()
}
return sk
}
```
### Modulus Switching
```go
// Dynamic modulus switching for optimization
func ModulusSwitch(ct *Ciphertext, targetLevel int) {
currentLevel := ct.Level()
for currentLevel > targetLevel {
// Scale down by one modulus
ct.Scale(ct, params.Q[currentLevel])
currentLevel--
}
ct.SetLevel(targetLevel)
}
```
### Multi-Key Operations
```go
// Parameters for multi-key homomorphic encryption
type MultiKeyParams struct {
BaseParams Parameters
NumParties int
Threshold int // For threshold decryption
}
func GenerateMultiKeyParams(numParties int, security int) MultiKeyParams {
// Increase parameters to handle key switching
baseParams := SelectParameters(security)
// Add extra modulus for relinearization
baseParams.LogP = append(baseParams.LogP, 61)
return MultiKeyParams{
BaseParams: baseParams,
NumParties: numParties,
Threshold: (numParties + 1) / 2,
}
}
```
## Troubleshooting
### Common Issues and Solutions
| Issue | Cause | Solution |
|-------|-------|----------|
| Decryption failure | Noise overflow | Increase Q or reduce circuit depth |
| Poor precision | Scale too small | Increase LogDefaultScale |
| Slow performance | N too large | Use minimal N for security |
| Large ciphertexts | Q too large | Optimize modulus chain |
| Bootstrap fails | Insufficient levels | Reserve more levels for bootstrapping |
## Conclusion
Proper parameter selection is crucial for:
- **Security**: Meeting cryptographic requirements
- **Correctness**: Ensuring computations succeed
- **Performance**: Optimizing speed and size
- **Practicality**: Balancing all constraints
Always validate parameters with security estimators and test thoroughly before deployment.
+779
View File
@@ -0,0 +1,779 @@
---
title: Usage Examples
description: Practical examples and tutorials for implementing lattice-based cryptography
---
# Usage Examples
Comprehensive collection of practical examples demonstrating real-world applications of lattice-based cryptography, from basic operations to complex protocols.
## Getting Started
### Installation
```bash
# Install the Lattice library
go get github.com/luxfi/lattice/v6
# Import required packages
import (
"github.com/luxfi/lattice/v6/core/rlwe"
"github.com/luxfi/lattice/v6/schemes/ckks"
"github.com/luxfi/lattice/v6/schemes/bgv"
"github.com/luxfi/lattice/v6/multiparty"
)
```
### Basic Setup
```go
package main
import (
"fmt"
"log"
"github.com/luxfi/lattice/v6/core/rlwe"
"github.com/luxfi/lattice/v6/schemes/ckks"
)
func main() {
// Initialize parameters for 128-bit security
params, err := ckks.NewParametersFromLiteral(
ckks.ParametersLiteral{
LogN: 14,
LogQ: []int{50, 40, 40, 40},
LogP: []int{60},
LogDefaultScale: 40,
Sigma: 3.2,
},
)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Ring dimension: %d\n", params.N())
fmt.Printf("Ciphertext levels: %d\n", params.MaxLevel())
fmt.Printf("Precision: %d bits\n", params.LogDefaultScale())
}
```
## Basic Homomorphic Operations
### Arithmetic on Encrypted Numbers
```go
func encryptedArithmetic() {
// Setup
params, _ := ckks.NewParametersFromLiteral(ckks.PN14QP438)
kgen := rlwe.NewKeyGenerator(params)
sk := kgen.GenSecretKeyNew()
pk := kgen.GenPublicKeyNew(sk)
rlk := kgen.GenRelinearizationKeyNew(sk)
evk := rlwe.NewMemEvaluationKeySet(rlk)
encoder := ckks.NewEncoder(params)
encryptor := rlwe.NewEncryptor(params, pk)
decryptor := rlwe.NewDecryptor(params, sk)
evaluator := ckks.NewEvaluator(params, evk)
// Prepare data
x := []complex128{1.5, 2.5, 3.5, 4.5}
y := []complex128{0.5, 1.5, 2.5, 3.5}
// Encode and encrypt
ptX := ckks.NewPlaintext(params, params.MaxLevel())
ptY := ckks.NewPlaintext(params, params.MaxLevel())
encoder.Encode(x, ptX)
encoder.Encode(y, ptY)
ctX, _ := encryptor.EncryptNew(ptX)
ctY, _ := encryptor.EncryptNew(ptY)
// Homomorphic operations
// Addition: z = x + y
ctSum, _ := evaluator.AddNew(ctX, ctY)
// Multiplication: z = x * y
ctProd, _ := evaluator.MulRelinNew(ctX, ctY)
evaluator.Rescale(ctProd, ctProd)
// Square: z = x^2
ctSquare, _ := evaluator.MulRelinNew(ctX, ctX)
evaluator.Rescale(ctSquare, ctSquare)
// Decrypt and decode results
ptSum := decryptor.DecryptNew(ctSum)
ptProd := decryptor.DecryptNew(ctProd)
ptSquare := decryptor.DecryptNew(ctSquare)
resSum := encoder.Decode(ptSum, params.LogSlots())
resProd := encoder.Decode(ptProd, params.LogSlots())
resSquare := encoder.Decode(ptSquare, params.LogSlots())
fmt.Println("x + y =", resSum[:4])
fmt.Println("x * y =", resProd[:4])
fmt.Println("x^2 =", resSquare[:4])
}
```
### Polynomial Evaluation
```go
func evaluatePolynomial() {
params, _ := ckks.NewParametersFromLiteral(ckks.PN14QP438)
// ... (setup as before)
// Evaluate f(x) = 3x^3 - 2x^2 + x - 5
coefficients := []complex128{-5, 1, -2, 3}
// Input values
x := []complex128{1.0, 2.0, 3.0, 4.0}
ptX := ckks.NewPlaintext(params, params.MaxLevel())
encoder.Encode(x, ptX)
ctX, _ := encryptor.EncryptNew(ptX)
// Horner's method: f(x) = -5 + x(1 + x(-2 + x(3)))
result := ckks.NewCiphertext(params, 1, params.MaxLevel())
// Start with highest coefficient
encoder.Encode([]complex128{3, 3, 3, 3}, result.Plaintext())
encryptor.EncryptZero(result)
evaluator.Add(result, coefficients[3], result)
for i := 2; i >= 0; i-- {
// result = result * x + coefficients[i]
evaluator.MulRelin(result, ctX, result)
evaluator.Rescale(result, result)
// Add constant
constant := make([]complex128, params.Slots())
for j := range constant {
constant[j] = coefficients[i]
}
ptConst := ckks.NewPlaintext(params, result.Level())
encoder.EncodeAtLevelNew(constant, result.Level(), ptConst)
evaluator.Add(result, ptConst, result)
}
// Decrypt result
ptResult := decryptor.DecryptNew(result)
values := encoder.Decode(ptResult, params.LogSlots())
fmt.Println("f(x) =", values[:4])
// Expected: f(1)=-3, f(2)=9, f(3)=49, f(4)=135
}
```
## Machine Learning Applications
### Encrypted Linear Regression
```go
type EncryptedLinearRegression struct {
params ckks.Parameters
evaluator ckks.Evaluator
encoder ckks.Encoder
}
func (lr *EncryptedLinearRegression) Predict(
ctWeights *ckks.Ciphertext,
ctFeatures []*ckks.Ciphertext,
) (*ckks.Ciphertext, error) {
// Compute y = w0 + w1*x1 + w2*x2 + ... + wn*xn
if len(ctFeatures) == 0 {
return nil, errors.New("no features provided")
}
// Initialize with bias (first weight)
result := ckks.NewCiphertext(lr.params, 1, ctWeights.Level())
lr.evaluator.Mul(ctWeights, ctFeatures[0], result)
// Add weighted features
for i := 1; i < len(ctFeatures); i++ {
temp := ckks.NewCiphertext(lr.params, 1, ctWeights.Level())
// Rotate weights to align with next feature
rotatedWeights := lr.evaluator.RotateNew(ctWeights, i)
// Multiply and add
lr.evaluator.Mul(rotatedWeights, ctFeatures[i], temp)
lr.evaluator.Add(result, temp, result)
}
// Rescale for precision management
lr.evaluator.Rescale(result, result)
return result, nil
}
// Training encrypted model using gradient descent
func (lr *EncryptedLinearRegression) TrainStep(
ctWeights *ckks.Ciphertext,
ctFeatures []*ckks.Ciphertext,
ctLabels *ckks.Ciphertext,
learningRate float64,
) (*ckks.Ciphertext, error) {
// Predict with current weights
predictions, _ := lr.Predict(ctWeights, ctFeatures)
// Compute error: error = predictions - labels
error := lr.evaluator.SubNew(predictions, ctLabels)
// Compute gradients
gradients := make([]*ckks.Ciphertext, len(ctFeatures))
for i, feature := range ctFeatures {
// gradient[i] = mean(error * feature[i])
gradients[i] = lr.evaluator.MulNew(error, feature)
lr.evaluator.Rescale(gradients[i], gradients[i])
}
// Update weights: w = w - learningRate * gradient
ptLR := ckks.NewPlaintext(lr.params, ctWeights.Level())
lr.encoder.Encode([]complex128{complex(learningRate, 0)}, ptLR)
for i, grad := range gradients {
scaledGrad := lr.evaluator.MulNew(grad, ptLR)
lr.evaluator.Rescale(scaledGrad, scaledGrad)
// Update specific weight
rotatedWeights := lr.evaluator.RotateNew(ctWeights, i)
lr.evaluator.Sub(rotatedWeights, scaledGrad, rotatedWeights)
// Rotate back
ctWeights = lr.evaluator.RotateNew(rotatedWeights, -i)
}
return ctWeights, nil
}
```
### Encrypted Neural Network Inference
```go
type EncryptedNeuralNetwork struct {
layers []EncryptedLayer
}
type EncryptedLayer interface {
Forward(input *ckks.Ciphertext) (*ckks.Ciphertext, error)
}
// Fully connected layer
type EncryptedDenseLayer struct {
weights *ckks.Ciphertext
bias *ckks.Ciphertext
eval ckks.Evaluator
}
func (l *EncryptedDenseLayer) Forward(input *ckks.Ciphertext) (*ckks.Ciphertext, error) {
// Compute output = weights @ input + bias
output := l.eval.MulRelinNew(l.weights, input)
l.eval.Rescale(output, output)
l.eval.Add(output, l.bias, output)
return output, nil
}
// ReLU activation using polynomial approximation
type EncryptedReLU struct {
eval ckks.Evaluator
polynomial []complex128
}
func (r *EncryptedReLU) Forward(input *ckks.Ciphertext) (*ckks.Ciphertext, error) {
// Approximate ReLU with polynomial
// ReLU(x) ≈ 0.5x + 0.25x^2 + 0.125x^3 for x ∈ [-2, 2]
x2 := r.eval.MulRelinNew(input, input)
r.eval.Rescale(x2, x2)
x3 := r.eval.MulRelinNew(x2, input)
r.eval.Rescale(x3, x3)
// Combine terms
result := r.eval.MulNew(input, 0.5)
r.eval.Add(result, r.eval.MulNew(x2, 0.25), result)
r.eval.Add(result, r.eval.MulNew(x3, 0.125), result)
return result, nil
}
// Run inference
func (nn *EncryptedNeuralNetwork) Predict(input *ckks.Ciphertext) (*ckks.Ciphertext, error) {
current := input
for _, layer := range nn.layers {
next, err := layer.Forward(current)
if err != nil {
return nil, err
}
current = next
}
return current, nil
}
```
## Private Information Retrieval
### Basic PIR Query
```go
func privateDatabaseQuery() {
// Setup BGV for exact computation
params, _ := bgv.NewParametersFromLiteral(
bgv.ParametersLiteral{
LogN: 13,
LogQ: []int{60, 60, 60},
PlaintextModulus: 65537,
},
)
// Database with 1024 entries
database := make([]uint64, 1024)
for i := range database {
database[i] = uint64(i * i) // Example data
}
// Client wants to query index 42 privately
queryIndex := 42
// Create one-hot encoded query vector
query := make([]uint64, len(database))
query[queryIndex] = 1
// Encrypt query
encoder := bgv.NewEncoder(params)
encryptor := bgv.NewEncryptor(params, pk)
ptQuery := bgv.NewPlaintext(params)
encoder.Encode(query, ptQuery)
ctQuery, _ := encryptor.EncryptNew(ptQuery)
// Server computes response
// result = sum(database[i] * query[i]) for all i
evaluator := bgv.NewEvaluator(params, evk)
ctResult := bgv.NewCiphertext(params, 1, params.MaxLevel())
for i, value := range database {
if value != 0 {
// Rotate query to align with database entry
rotated := evaluator.RotateNew(ctQuery, i)
// Multiply by database value
evaluator.MulScalar(rotated, value, rotated)
// Add to result
evaluator.Add(ctResult, rotated, ctResult)
}
}
// Client decrypts result
ptResult := decryptor.DecryptNew(ctResult)
result := encoder.DecodeUint(ptResult)
fmt.Printf("Database[%d] = %d\n", queryIndex, result[0])
}
```
## Multiparty Computation
### Threshold Decryption
```go
func thresholdDecryption() {
params, _ := ckks.NewParametersFromLiteral(ckks.PN14QP438)
// Setup: 3 parties, threshold = 2
numParties := 3
threshold := 2
// Each party generates their secret key share
parties := make([]*Party, numParties)
for i := range parties {
parties[i] = &Party{
ID: i,
SK: rlwe.NewKeyGenerator(params).GenSecretKeyNew(),
}
}
// Threshold key generation protocol
tkg := multiparty.NewTKGProtocol(params)
// Each party creates their share
shares := make([]*multiparty.TKGShare, numParties)
for i, party := range parties {
shares[i] = tkg.GenShare(party.SK)
}
// Aggregate to get collective public key
collectivePK := tkg.AggregateShares(shares)
// Encrypt data with collective public key
encoder := ckks.NewEncoder(params)
encryptor := rlwe.NewEncryptor(params, collectivePK)
data := []complex128{1.23, 4.56, 7.89}
pt := ckks.NewPlaintext(params, params.MaxLevel())
encoder.Encode(data, pt)
ct, _ := encryptor.EncryptNew(pt)
// Threshold decryption with any 2 parties
pcks := multiparty.NewPCKSProtocol(params)
// Select subset of parties (meets threshold)
activeParties := parties[:threshold]
// Generate decryption shares
decShares := make([]*multiparty.PCKSShare, threshold)
for i, party := range activeParties {
decShares[i] = pcks.GenShare(party.SK, ct)
}
// Combine shares to decrypt
ptResult := pcks.AggregateShares(decShares, ct)
result := encoder.Decode(ptResult, params.LogSlots())
fmt.Println("Decrypted:", result[:3])
}
```
### Secure Multiparty Training
```go
type SecureMLTraining struct {
params ckks.Parameters
parties []*MLParty
protocol *multiparty.Protocol
}
type MLParty struct {
ID int
SK *rlwe.SecretKey
DataSet [][]float64
LocalModel *ckks.Ciphertext
}
func (sml *SecureMLTraining) FederatedAveraging() (*ckks.Ciphertext, error) {
// Each party trains locally and encrypts their model
encryptedModels := make([]*ckks.Ciphertext, len(sml.parties))
for i, party := range sml.parties {
// Local training (in plaintext)
localWeights := party.TrainLocal()
// Encrypt local model
pt := ckks.NewPlaintext(sml.params, sml.params.MaxLevel())
encoder.Encode(localWeights, pt)
encryptedModels[i], _ = encryptor.EncryptNew(pt)
}
// Secure aggregation
globalModel := sml.SecureAggregate(encryptedModels)
// Collaborative decryption
return sml.CollectiveDecrypt(globalModel)
}
func (sml *SecureMLTraining) SecureAggregate(models []*ckks.Ciphertext) *ckks.Ciphertext {
// Average encrypted models
result := models[0].CopyNew()
for i := 1; i < len(models); i++ {
evaluator.Add(result, models[i], result)
}
// Divide by number of parties
scale := 1.0 / float64(len(models))
evaluator.MulScalar(result, scale, result)
evaluator.Rescale(result, result)
return result
}
```
## Financial Applications
### Private Portfolio Analysis
```go
type PrivatePortfolio struct {
holdings map[string]*ckks.Ciphertext // Encrypted quantities
evaluator ckks.Evaluator
}
func (p *PrivatePortfolio) CalculateValue(prices map[string]float64) *ckks.Ciphertext {
var totalValue *ckks.Ciphertext
for asset, encryptedQuantity := range p.holdings {
price := prices[asset]
// value = quantity * price
value := p.evaluator.MulScalarNew(encryptedQuantity, price)
p.evaluator.Rescale(value, value)
if totalValue == nil {
totalValue = value
} else {
p.evaluator.Add(totalValue, value, totalValue)
}
}
return totalValue
}
func (p *PrivatePortfolio) CalculateRisk(
correlationMatrix [][]float64,
volatilities []float64,
) *ckks.Ciphertext {
// Portfolio risk = sqrt(w^T * Σ * w)
// where Σ is covariance matrix
assets := make([]string, 0, len(p.holdings))
weights := make([]*ckks.Ciphertext, 0, len(p.holdings))
for asset, holding := range p.holdings {
assets = append(assets, asset)
weights = append(weights, holding)
}
// Compute weighted covariance
risk := ckks.NewCiphertext(p.evaluator.Parameters(), 1, weights[0].Level())
for i := range assets {
for j := range assets {
// cov[i,j] = correlation[i,j] * vol[i] * vol[j]
cov := correlationMatrix[i][j] * volatilities[i] * volatilities[j]
// risk += w[i] * w[j] * cov[i,j]
term := p.evaluator.MulNew(weights[i], weights[j])
p.evaluator.Rescale(term, term)
p.evaluator.MulScalar(term, cov, term)
p.evaluator.Add(risk, term, risk)
}
}
// Note: Square root would require polynomial approximation
return risk
}
```
## Advanced Techniques
### Bootstrapping Example
```go
func bootstrappingExample() {
// Parameters with bootstrapping support
params, _ := ckks.NewParametersFromLiteral(
ckks.ParametersLiteral{
LogN: 16,
LogQ: []int{
// Computation levels
60, 50, 50, 50, 50,
// Bootstrapping levels
60, 60, 60, 60, 60, 60, 60, 60,
},
LogP: []int{61, 61, 61},
LogDefaultScale: 50,
H: 192,
},
)
// Setup bootstrapper
btpParams := bootstrapping.ParametersLiteral{
LogN: params.LogN(),
LogSlots: params.LogSlots(),
H: 192,
Sigma: params.Sigma(),
}
bootstrapper, _ := bootstrapping.NewBootstrapper(params, btpParams, evk)
// Perform deep computation
ct := encryptInitialData()
for i := 0; i < 100; i++ {
// Complex computation
ct = evaluator.MulRelinNew(ct, ct)
evaluator.Rescale(ct, ct)
// Check if bootstrapping needed
if ct.Level() == 0 {
fmt.Printf("Bootstrapping at iteration %d\n", i)
ct, _ = bootstrapper.Bootstrap(ct)
}
}
// Decrypt final result
result := decrypt(ct)
fmt.Println("Result after 100 multiplications:", result)
}
```
### Custom Polynomial Evaluation
```go
func evaluateCustomFunction() {
// Approximate sin(x) using Chebyshev polynomials
// sin(x) ≈ x - x³/6 + x⁵/120 - x⁷/5040 for x ∈ [-π, π]
coeffs := []float64{
0, // x⁰
1, // x¹
0, // x²
-1.0/6, // x³
0, // x⁴
1.0/120, // x⁵
0, // x⁶
-1.0/5040, // x⁷
}
// Create polynomial evaluator
polyEval := ckks.NewPolynomialEvaluator(params, evaluator)
// Input values
x := []complex128{0, 0.5, 1.0, 1.5}
ptX := encode(x)
ctX := encrypt(ptX)
// Evaluate polynomial
ctResult, _ := polyEval.Evaluate(ctX, coeffs)
// Compare with actual sin(x)
result := decrypt(ctResult)
fmt.Println("Approximate sin(x):", result)
fmt.Println("Actual sin(x):", []float64{
math.Sin(0), math.Sin(0.5), math.Sin(1.0), math.Sin(1.5),
})
}
```
## Performance Optimization Tips
### Batching Operations
```go
func efficientBatching() {
// Process multiple data items in single ciphertext
batchSize := params.Slots() // Use all available slots
// Pack data efficiently
data := make([]complex128, batchSize)
for i := 0; i < actualDataSize; i++ {
data[i] = actualData[i]
}
// Remaining slots stay zero
// Single encryption for entire batch
pt := encode(data)
ct := encrypt(pt)
// Operations apply to all slots simultaneously
ctSquared := evaluator.MulRelinNew(ct, ct)
evaluator.Rescale(ctSquared, ctSquared)
// Decrypt entire batch
result := decrypt(ctSquared)
// Use first actualDataSize elements
}
```
### Memory Management
```go
func memoryEfficientComputation() {
// Reuse ciphertexts to reduce memory
ct1 := encrypt(data1)
ct2 := encrypt(data2)
// In-place operations
evaluator.Add(ct1, ct2, ct1) // Result overwrites ct1
evaluator.MulRelin(ct1, ct1, ct1) // Square in-place
evaluator.Rescale(ct1, ct1)
// Manual memory cleanup for large computations
runtime.GC()
// Use object pools for repeated allocations
ctPool := sync.Pool{
New: func() interface{} {
return ckks.NewCiphertext(params, 1, params.MaxLevel())
},
}
// Get from pool
temp := ctPool.Get().(*ckks.Ciphertext)
// Use temp...
// Return to pool
ctPool.Put(temp)
}
```
## Testing and Validation
### Unit Testing Homomorphic Operations
```go
func TestHomomorphicAddition(t *testing.T) {
// Setup
params, _ := ckks.NewParametersFromLiteral(testParams)
// ... initialize crypto components
// Test data
a := []complex128{1.0, 2.0, 3.0, 4.0}
b := []complex128{5.0, 6.0, 7.0, 8.0}
expected := []complex128{6.0, 8.0, 10.0, 12.0}
// Encrypt
ctA := encryptVector(a)
ctB := encryptVector(b)
// Homomorphic addition
ctSum := evaluator.AddNew(ctA, ctB)
// Decrypt and verify
result := decryptVector(ctSum)
for i := range expected {
if math.Abs(real(result[i] - expected[i])) > 0.01 {
t.Errorf("Mismatch at %d: got %v, want %v",
i, result[i], expected[i])
}
}
}
```
### Benchmarking
```go
func BenchmarkHomomorphicMultiplication(b *testing.B) {
// Setup
params, _ := ckks.NewParametersFromLiteral(ckks.PN14QP438)
// ... initialize
ct1 := encrypt(randomData())
ct2 := encrypt(randomData())
b.ResetTimer()
for i := 0; i < b.N; i++ {
result := evaluator.MulRelinNew(ct1, ct2)
evaluator.Rescale(result, result)
}
}
```
## Conclusion
These examples demonstrate the versatility of lattice-based cryptography for:
- **Privacy-preserving computation**: Process encrypted data without decryption
- **Machine learning**: Train and evaluate models on encrypted data
- **Financial analysis**: Perform calculations on sensitive financial data
- **Multiparty protocols**: Enable secure collaboration without sharing raw data
Key takeaways:
1. Always manage noise levels and precision
2. Use batching for efficiency
3. Implement proper key management
4. Test thoroughly with realistic data
5. Monitor performance and optimize as needed
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import { docs } from "@/.source"
import { loader } from "fumadocs-core/source"
// Create a single source instance that is reused
// This prevents circular references and stack overflow issues
let _source: ReturnType<typeof loader> | null = null
export function getSource() {
if (!_source) {
_source = loader({
baseUrl: "/docs",
source: docs.toFumadocsSource(),
})
}
return _source
}
export const source = getSource()
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import type { MDXComponents } from "mdx/types"
import defaultMdxComponents from "fumadocs-ui/mdx"
export function useMDXComponents(components: MDXComponents): MDXComponents {
return {
...defaultMdxComponents,
...components,
}
}
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import { createMDX } from "fumadocs-mdx/next"
/** @type {import('next').NextConfig} */
const config = {
output: 'export',
reactStrictMode: true,
typescript: {
ignoreBuildErrors: true,
},
experimental: {
webpackBuildWorker: true,
},
images: {
unoptimized: true,
},
}
const withMDX = createMDX()
export default withMDX(config)
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{
"name": "@luxfi/lattice-docs",
"version": "1.0.0",
"private": true,
"scripts": {
"dev": "next dev --port 3001",
"build": "fumadocs-mdx && TURBOPACK=0 next build",
"export": "TURBOPACK=0 next build",
"start": "next start",
"lint": "next lint",
"postinstall": "fumadocs-mdx"
},
"dependencies": {
"fumadocs-core": "^15.8.5",
"fumadocs-mdx": "^12.0.3",
"fumadocs-ui": "^15.8.5",
"lucide-react": "^0.468.0",
"next": "16.0.1",
"react": "19.2.0",
"react-dom": "19.2.0",
"tailwindcss": "^4.1.16",
"zod": "^3.24.1"
},
"devDependencies": {
"@tailwindcss/postcss": "^4.1.16",
"@types/node": "^22.10.2",
"@types/react": "^19.0.1",
"@types/react-dom": "^19.0.2",
"autoprefixer": "^10.4.20",
"postcss": "^8.4.49",
"rehype-pretty-code": "^0.14.1",
"shiki": "^1.27.2",
"typescript": "^5.7.2"
},
"packageManager": "[email protected]"
}
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module.exports = {
plugins: {
'@tailwindcss/postcss': {},
autoprefixer: {},
},
}
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import {
defineConfig,
defineDocs,
} from "fumadocs-mdx/config"
import rehypePrettyCode from "rehype-pretty-code"
export default defineConfig({
mdxOptions: {
rehypePlugins: [
[
rehypePrettyCode,
{
theme: {
dark: "github-dark-dimmed",
light: "github-light",
},
keepBackground: false,
defaultLang: "go",
},
],
],
},
})
export const docs = defineDocs({
dir: "content/docs",
})
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{
"compilerOptions": {
"lib": [
"dom",
"dom.iterable",
"esnext"
],
"allowJs": true,
"skipLibCheck": true,
"strict": true,
"noEmit": true,
"esModuleInterop": true,
"module": "esnext",
"moduleResolution": "bundler",
"resolveJsonModule": true,
"isolatedModules": true,
"jsx": "react-jsx",
"incremental": true,
"plugins": [
{
"name": "next"
}
],
"paths": {
"@/*": [
"./*"
]
},
"target": "ES2017"
},
"include": [
"next-env.d.ts",
"**/*.ts",
"**/*.tsx",
".next/types/**/*.ts",
".next/dev/types/**/*.ts"
],
"exclude": [
"node_modules"
]
}