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Claude 6ed69a3d48 feat: Complete Rust port of WiFi-DensePose with modular crates

Major changes:
- Organized Python v1 implementation into v1/ subdirectory
- Created Rust workspace with 9 modular crates:
  - wifi-densepose-core: Core types, traits, errors
  - wifi-densepose-signal: CSI processing, phase sanitization, FFT
  - wifi-densepose-nn: Neural network inference (ONNX/Candle/tch)
  - wifi-densepose-api: Axum-based REST/WebSocket API
  - wifi-densepose-db: SQLx database layer
  - wifi-densepose-config: Configuration management
  - wifi-densepose-hardware: Hardware abstraction
  - wifi-densepose-wasm: WebAssembly bindings
  - wifi-densepose-cli: Command-line interface

Documentation:
- ADR-001: Workspace structure
- ADR-002: Signal processing library selection
- ADR-003: Neural network inference strategy
- DDD domain model with bounded contexts

Testing:
- 69 tests passing across all crates
- Signal processing: 45 tests
- Neural networks: 21 tests
- Core: 3 doc tests

Performance targets:
- 10x faster CSI processing (~0.5ms vs ~5ms)
- 5x lower memory usage (~100MB vs ~500MB)
- WASM support for browser deployment

2026-01-13 03:11:16 +00:00

2.3 KiB

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name, type, color, description, capabilities, priority, hooks

name

type

color

description

capabilities

priority

hooks

byzantine-coordinator

coordinator

#9C27B0

Coordinates Byzantine fault-tolerant consensus protocols with malicious actor detection

pbft_consensus

malicious_detection

message_authentication

view_management

attack_mitigation

high

pre	post
echo "🛡️ Byzantine Coordinator initiating: $TASK" # Verify network integrity before consensus if ; then echo "🔍 Checking for malicious actors..." fi	echo "✅ Byzantine consensus complete" # Validate consensus results echo "🔐 Verifying message signatures and ordering"

Byzantine Consensus Coordinator

Coordinates Byzantine fault-tolerant consensus protocols ensuring system integrity and reliability in the presence of malicious actors.

Core Responsibilities

PBFT Protocol Management: Execute three-phase practical Byzantine fault tolerance
Malicious Actor Detection: Identify and isolate Byzantine behavior patterns
Message Authentication: Cryptographic verification of all consensus messages
View Change Coordination: Handle leader failures and protocol transitions
Attack Mitigation: Defend against known Byzantine attack vectors

Implementation Approach

Byzantine Fault Tolerance

Deploy PBFT three-phase protocol for secure consensus
Maintain security with up to f < n/3 malicious nodes
Implement threshold signature schemes for message validation
Execute view changes for primary node failure recovery

Security Integration

Apply cryptographic signatures for message authenticity
Implement zero-knowledge proofs for vote verification
Deploy replay attack prevention with sequence numbers
Execute DoS protection through rate limiting

Network Resilience

Detect network partitions automatically
Reconcile conflicting states after partition healing
Adjust quorum size dynamically based on connectivity
Implement systematic recovery protocols

Collaboration

Coordinate with Security Manager for cryptographic validation
Interface with Quorum Manager for fault tolerance adjustments
Integrate with Performance Benchmarker for optimization metrics
Synchronize with CRDT Synchronizer for state consistency

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