Comprehensive architecture decision records for integrating ruvnet/ruvector
into wifi-densepose, covering:
- ADR-002: Master integration strategy (phased rollout, new crate design)
- ADR-003: RVF cognitive containers for CSI data persistence
- ADR-004: HNSW vector search replacing fixed-threshold detection
- ADR-005: SONA self-learning with LoRA + EWC++ for online adaptation
- ADR-006: GNN-enhanced pattern recognition with temporal modeling
- ADR-007: Post-quantum cryptography (ML-DSA-65 hybrid signatures)
- ADR-008: Raft consensus for multi-AP distributed coordination
- ADR-009: RVF WASM runtime for edge/browser/IoT deployment
- ADR-010: Witness chains for tamper-evident audit trails
- ADR-011: Mock elimination and proof-of-reality (fixes np.random.rand
placeholders, ships CSI capture + SHA-256 verified pipeline)
- ADR-012: ESP32 CSI sensor mesh ($54 starter kit specification)
- ADR-013: Feature-level sensing on commodity gear (zero-cost RSSI path)
ADR-011 directly addresses the credibility gap by cataloging every
mock/placeholder in the Python codebase and specifying concrete fixes.
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
216 lines
11 KiB
Markdown
216 lines
11 KiB
Markdown
# ADR-007: Post-Quantum Cryptography for Secure Sensing
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## Status
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Proposed
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## Date
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2026-02-28
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## Context
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### Threat Model
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WiFi-DensePose processes data that can reveal:
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- **Human presence/absence** in private spaces (surveillance risk)
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- **Health indicators** via breathing/heartbeat detection (medical privacy)
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- **Movement patterns** (behavioral profiling)
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- **Building occupancy** (physical security intelligence)
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In disaster scenarios (wifi-densepose-mat), the stakes are even higher:
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- **Triage classifications** affect rescue priority (life-or-death decisions)
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- **Survivor locations** are operationally sensitive
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- **Detection audit trails** may be used in legal proceedings (liability)
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- **False negatives** (missed survivors) could be forensically investigated
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Current security: The system uses standard JWT (HS256) for API authentication and has no cryptographic protection on data at rest, model integrity, or detection audit trails.
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### Quantum Threat Timeline
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NIST estimates cryptographically relevant quantum computers could emerge by 2030-2035. Data captured today with classical encryption may be decrypted retroactively ("harvest now, decrypt later"). For a system that may be deployed for decades in infrastructure, post-quantum readiness is prudent.
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### RuVector's Crypto Stack
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RuVector provides a layered cryptographic system:
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| Algorithm | Purpose | Standard | Quantum Resistant |
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|-----------|---------|----------|-------------------|
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| ML-DSA-65 | Digital signatures | FIPS 204 | Yes (lattice-based) |
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| Ed25519 | Digital signatures | RFC 8032 | No (classical fallback) |
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| SLH-DSA-128s | Digital signatures | FIPS 205 | Yes (hash-based) |
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| SHAKE-256 | Hashing | FIPS 202 | Yes |
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| AES-256-GCM | Symmetric encryption | FIPS 197 | Yes (Grover's halves, still 128-bit) |
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## Decision
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We will integrate RuVector's cryptographic layer to provide defense-in-depth for WiFi-DensePose data, using a **hybrid classical+PQ** approach where both Ed25519 and ML-DSA-65 signatures are applied (belt-and-suspenders until PQ algorithms mature).
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### Cryptographic Scope
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```
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┌──────────────────────────────────────────────────────────────────┐
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│ Cryptographic Protection Layers │
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├──────────────────────────────────────────────────────────────────┤
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│ │
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│ 1. MODEL INTEGRITY │
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│ ┌─────────────────────────────────────────────────────┐ │
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│ │ Model weights signed with ML-DSA-65 + Ed25519 │ │
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│ │ Signature verified at load time → reject tampered │ │
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│ │ SONA adaptations co-signed with device key │ │
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│ └─────────────────────────────────────────────────────┘ │
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│ │
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│ 2. DATA AT REST (RVF containers) │
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│ ┌─────────────────────────────────────────────────────┐ │
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│ │ CSI vectors encrypted with AES-256-GCM │ │
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│ │ Container integrity via SHAKE-256 Merkle tree │ │
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│ │ Key management: per-container keys, sealed to device │ │
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│ └─────────────────────────────────────────────────────┘ │
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│ │
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│ 3. DATA IN TRANSIT │
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│ ┌─────────────────────────────────────────────────────┐ │
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│ │ API: TLS 1.3 with PQ key exchange (ML-KEM-768) │ │
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│ │ WebSocket: Same TLS channel │ │
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│ │ Multi-AP sync: mTLS with device certificates │ │
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│ └─────────────────────────────────────────────────────┘ │
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│ │
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│ 4. AUDIT TRAIL (witness chains - see ADR-010) │
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│ ┌─────────────────────────────────────────────────────┐ │
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│ │ Every detection event hash-chained with SHAKE-256 │ │
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│ │ Chain anchors signed with ML-DSA-65 │ │
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│ │ Cross-device attestation via SLH-DSA-128s │ │
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│ └─────────────────────────────────────────────────────┘ │
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│ │
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│ 5. DEVICE IDENTITY │
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│ ┌─────────────────────────────────────────────────────┐ │
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│ │ Each sensing device has a key pair (ML-DSA-65) │ │
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│ │ Device attestation proves hardware integrity │ │
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│ │ Key rotation schedule: 90 days (or on compromise) │ │
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│ └─────────────────────────────────────────────────────┘ │
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└──────────────────────────────────────────────────────────────────┘
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```
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### Hybrid Signature Scheme
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```rust
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/// Hybrid signature combining classical Ed25519 with PQ ML-DSA-65
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pub struct HybridSignature {
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/// Classical Ed25519 signature (64 bytes)
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ed25519_sig: [u8; 64],
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/// Post-quantum ML-DSA-65 signature (3309 bytes)
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ml_dsa_sig: Vec<u8>,
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/// Signer's public key fingerprint (SHAKE-256, 32 bytes)
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signer_fingerprint: [u8; 32],
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/// Timestamp of signing
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timestamp: u64,
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}
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impl HybridSignature {
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/// Verify requires BOTH signatures to be valid
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pub fn verify(&self, message: &[u8], ed25519_pk: &Ed25519PublicKey,
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ml_dsa_pk: &MlDsaPublicKey) -> Result<bool, CryptoError> {
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let ed25519_valid = ed25519_pk.verify(message, &self.ed25519_sig)?;
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let ml_dsa_valid = ml_dsa_pk.verify(message, &self.ml_dsa_sig)?;
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// Both must pass (defense in depth)
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Ok(ed25519_valid && ml_dsa_valid)
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}
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}
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```
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### Model Integrity Verification
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```rust
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/// Verify model weights have not been tampered with
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pub fn verify_model_integrity(model_container: &ModelContainer) -> Result<(), SecurityError> {
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// 1. Extract embedded signature from container
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let signature = model_container.crypto_segment().signature()?;
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// 2. Compute SHAKE-256 hash of weight data
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let weight_hash = shake256(model_container.weights_segment().data());
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// 3. Verify hybrid signature
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let publisher_keys = load_publisher_keys()?;
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if !signature.verify(&weight_hash, &publisher_keys.ed25519, &publisher_keys.ml_dsa)? {
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return Err(SecurityError::ModelTampered {
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expected_signer: publisher_keys.fingerprint(),
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container_path: model_container.path().to_owned(),
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});
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}
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Ok(())
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}
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```
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### CSI Data Encryption
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For privacy-sensitive deployments, CSI vectors can be encrypted at rest:
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```rust
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/// Encrypt CSI vectors for storage in RVF container
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pub struct CsiEncryptor {
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/// AES-256-GCM key (derived from device key + container salt)
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key: Aes256GcmKey,
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}
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impl CsiEncryptor {
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/// Encrypt a CSI feature vector
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/// Note: HNSW search operates on encrypted vectors using
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/// distance-preserving encryption (approximate, configurable trade-off)
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pub fn encrypt_vector(&self, vector: &[f32]) -> EncryptedVector {
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let nonce = generate_nonce();
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let plaintext = bytemuck::cast_slice::<f32, u8>(vector);
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let ciphertext = aes_256_gcm_encrypt(&self.key, &nonce, plaintext);
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EncryptedVector { ciphertext, nonce }
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}
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}
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```
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### Performance Impact
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| Operation | Without Crypto | With Crypto | Overhead |
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|-----------|---------------|-------------|----------|
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| Model load | 50 ms | 52 ms | +2 ms (signature verify) |
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| Vector insert | 0.1 ms | 0.15 ms | +0.05 ms (encrypt) |
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| HNSW search | 0.3 ms | 0.35 ms | +0.05 ms (decrypt top-K) |
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| Container open | 10 ms | 12 ms | +2 ms (integrity check) |
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| Detection event logging | 0.01 ms | 0.5 ms | +0.49 ms (hash chain) |
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### Feature Flags
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```toml
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[features]
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default = []
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crypto-classical = ["ed25519-dalek"] # Ed25519 only
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crypto-pq = ["pqcrypto-dilithium", "pqcrypto-sphincsplus"] # ML-DSA + SLH-DSA
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crypto-hybrid = ["crypto-classical", "crypto-pq"] # Both (recommended)
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crypto-encrypt = ["aes-gcm"] # Data-at-rest encryption
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crypto-full = ["crypto-hybrid", "crypto-encrypt"]
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```
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## Consequences
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### Positive
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- **Future-proof**: Lattice-based signatures resist quantum attacks
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- **Tamper detection**: Model poisoning and data manipulation are detectable
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- **Privacy compliance**: Encrypted CSI data meets GDPR/HIPAA requirements
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- **Forensic integrity**: Signed audit trails are admissible as evidence
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- **Low overhead**: <1ms per operation for most crypto operations
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### Negative
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- **Signature size**: ML-DSA-65 signatures are 3.3 KB vs 64 bytes for Ed25519
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- **Key management complexity**: Device key provisioning, rotation, revocation
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- **HNSW on encrypted data**: Distance-preserving encryption is approximate; search recall may degrade
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- **Dependency weight**: PQ crypto libraries add ~2 MB to binary
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- **Standards maturity**: FIPS 204/205 are finalized but implementations are evolving
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## References
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- [FIPS 204: ML-DSA (Module-Lattice Digital Signature)](https://csrc.nist.gov/pubs/fips/204/final)
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- [FIPS 205: SLH-DSA (Stateless Hash-Based Digital Signature)](https://csrc.nist.gov/pubs/fips/205/final)
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- [FIPS 202: SHA-3 / SHAKE](https://csrc.nist.gov/pubs/fips/202/final)
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- [RuVector Crypto Implementation](https://github.com/ruvnet/ruvector)
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- ADR-002: RuVector RVF Integration Strategy
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- ADR-010: Witness Chains for Audit Trail Integrity
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