GeoVAN is an enterprise-grade Vehicular Ad-hoc Network (VANET) platform that provides real-time vehicle tracking, security validation, trust scoring, and anomaly detection. Built with Rust for maximum performance and security, it's designed to handle thousands of vehicles with sub-millisecond latency while maintaining cryptographic integrity and privacy.
- 🔐 Cryptographic Security: ECDSA signatures, certificate validation, and replay protection
- 🛡️ Trust Scoring: AI-powered anomaly detection and trust computation
- ⚡ High Performance: Rust backend with <1ms latency for 10K+ vehicles
- 🌐 Real-time Visualization: React-based dashboard with live maps and analytics
- 🔒 Privacy Protection: Pseudonym rotation and zero-knowledge proofs
- 📊 Advanced Analytics: Machine learning for traffic pattern analysis
- 🚀 Scalable Architecture: Microservices with horizontal scaling
- 🔄 Fault Tolerance: Automatic failover and load balancing
graph TB
subgraph "Vehicle Layer"
V1[Vehicle 1]
V2[Vehicle 2]
VN[Vehicle N]
GPS[GPS Module]
OBD[OBD-II]
end
subgraph "Communication Layer"
DSRC[DSRC/WiFi]
CELL[4G/5G]
SAT[Satellite]
end
subgraph "Edge Layer"
RSU[RSU Node]
EDGE[Edge Gateway]
end
subgraph "Core Infrastructure"
LB[Load Balancer]
API[API Gateway]
AUTH[Auth Service]
MSG[Message Broker]
end
subgraph "Microservices"
TRACK[Tracking Service]
TRUST[Trust Service]
ANALYTICS[Analytics Service]
ALERTS[Alert Service]
end
subgraph "Data Layer"
CACHE[Redis Cache]
DB[(PostgreSQL)]
TS[(TimescaleDB)]
QUEUE[RabbitMQ]
end
subgraph "Frontend"
WEB[Web Dashboard]
MOBILE[Mobile App]
API_CLIENT[API Clients]
end
V1 --> DSRC
V2 --> CELL
VN --> SAT
GPS --> V1
OBD --> V1
DSRC --> RSU
CELL --> EDGE
SAT --> EDGE
RSU --> LB
EDGE --> LB
LB --> API
API --> AUTH
API --> MSG
MSG --> TRACK
MSG --> TRUST
MSG --> ANALYTICS
MSG --> ALERTS
TRACK --> CACHE
TRUST --> DB
ANALYTICS --> TS
ALERTS --> QUEUE
TRACK --> WEB
TRUST --> WEB
ANALYTICS --> WEB
ALERTS --> WEB
sequenceDiagram
participant V as Vehicle
participant RSU as RSU Node
participant API as API Gateway
participant AUTH as Auth Service
participant TRACK as Tracking Service
participant TRUST as Trust Service
participant DB as Database
participant WS as WebSocket
participant UI as Frontend
V->>RSU: GPS + OBD Data + Signature
RSU->>API: Encrypted Message
API->>AUTH: Validate Certificate
AUTH->>API: Auth Result
alt Valid Certificate
API->>TRACK: Decrypted Position
TRACK->>TRUST: Position + Metadata
TRUST->>DB: Store + Compute Trust
TRUST->>TRACK: Trust Score
TRACK->>WS: Position + Trust
WS->>UI: Real-time Update
else Invalid Certificate
API->>TRACK: Reject Message
TRACK->>DB: Log Security Event
end
graph LR
subgraph "Vehicle Security"
PKI[PKI Certificate]
SIG[ECDSA Signature]
ENC[AES-256 Encryption]
HASH[SHA-256 Hash]
end
subgraph "Network Security"
TLS[TLS 1.3]
VPN[WireGuard VPN]
FIREWALL[Network Firewall]
IDS[Intrusion Detection]
end
subgraph "Application Security"
JWT[JWT Tokens]
RBAC[Role-Based Access]
RATE[Rate Limiting]
VALID[Input Validation]
end
subgraph "Data Security"
ENCRYPT[Data Encryption]
BACKUP[Secure Backup]
AUDIT[Audit Logging]
COMPLIANCE[GDPR/CCPA]
end
PKI --> SIG
SIG --> ENC
ENC --> HASH
TLS --> VPN
VPN --> FIREWALL
FIREWALL --> IDS
JWT --> RBAC
RBAC --> RATE
RATE --> VALID
ENCRYPT --> BACKUP
BACKUP --> AUDIT
AUDIT --> COMPLIANCE
- ECDSA Signatures: 256-bit elliptic curve digital signatures for message authenticity
- Certificate Validation: X.509 certificate chain validation with OCSP stapling
- Replay Protection: Monotonic sequence numbers and timestamp validation
- Message Integrity: SHA-256 hashing with HMAC for tamper detection
- Encryption: AES-256-GCM for sensitive data in transit and at rest
- Pseudonym Rotation: Automatic vehicle ID rotation every 5 minutes
- Zero-Knowledge Proofs: Prove location without revealing exact coordinates
- Differential Privacy: Add noise to location data for privacy preservation
- Data Anonymization: Remove PII before storage and analysis
- Trust Scoring: Multi-factor trust computation (0.0 - 1.0 scale)
- Behavioral Analysis: ML-based anomaly detection for suspicious patterns
- Reputation System: Vehicle reputation based on historical behavior
- Threat Intelligence: Real-time threat feed integration
| Metric | Current | Target | Architecture |
|---|---|---|---|
| Vehicles | 1,000 | 100,000 | Horizontal scaling |
| Messages/sec | 10,000 | 1,000,000 | Async processing |
| Latency | <10ms | <1ms | Rust + Redis |
| Throughput | 100 MB/s | 10 GB/s | Load balancing |
| Uptime | 99.9% | 99.99% | Fault tolerance |
- Framework: Actix-web for high-performance HTTP
- Database: PostgreSQL + TimescaleDB for time-series data
- Cache: Redis for sub-millisecond response times
- Message Queue: RabbitMQ for reliable message delivery
- Authentication: JWT + OAuth2 with PKI integration
- Framework: React 18 with TypeScript
- State Management: Redux Toolkit + RTK Query
- Maps: Mapbox GL JS for high-performance mapping
- UI Components: Material-UI with custom design system
- Real-time: WebSocket with automatic reconnection
- Containerization: Docker + Kubernetes
- Monitoring: Prometheus + Grafana
- Logging: ELK Stack (Elasticsearch, Logstash, Kibana)
- CI/CD: GitHub Actions with automated testing
syntax = "proto3";
package geovan.v2;
import "google/protobuf/timestamp.proto";
import "google/protobuf/any.proto";
// Enhanced vehicle position with security
message VehiclePosition {
// Core fields
string vehicle_id = 1; // Ephemeral pseudonym
string certificate_id = 2; // X.509 certificate identifier
Vec3 position = 3; // WGS84 + altitude
Vec3 velocity = 4; // Speed + direction
float heading = 5; // Degrees from true north
google.protobuf.Timestamp timestamp = 6;
uint64 sequence = 7; // Monotonic sequence
// Security fields
bytes signature = 8; // ECDSA signature
bytes encrypted_data = 9; // AES-256 encrypted payload
string nonce = 10; // Cryptographic nonce
// Metadata
VehicleMetadata metadata = 11;
repeated SensorReading sensors = 12;
TrustMetrics trust = 13;
}
// 3D position with accuracy
message Vec3 {
double lat = 1; // Latitude (WGS84)
double lon = 2; // Longitude (WGS84)
double alt = 3; // Altitude (meters)
float accuracy = 4; // Position accuracy (meters)
float hdop = 5; // Horizontal dilution of precision
float vdop = 6; // Vertical dilution of precision
}
// Vehicle metadata
message VehicleMetadata {
string make = 1; // Vehicle manufacturer
string model = 2; // Vehicle model
string year = 3; // Manufacturing year
VehicleType type = 4; // Vehicle classification
repeated string capabilities = 5; // VANET capabilities
}
// Sensor readings
message SensorReading {
SensorType type = 1; // Sensor type
float value = 2; // Sensor value
float accuracy = 3; // Measurement accuracy
google.protobuf.Timestamp timestamp = 4;
}
// Trust metrics
message TrustMetrics {
float overall_score = 1; // 0.0 - 1.0 trust score
float behavior_score = 2; // Behavioral trust
float certificate_score = 3; // Certificate validity
float history_score = 4; // Historical trust
repeated string flags = 5; // Trust flags
uint64 last_update = 6; // Last trust update
}
// Enums
enum VehicleType {
UNKNOWN = 0;
PASSENGER_CAR = 1;
TRUCK = 2;
BUS = 3;
MOTORCYCLE = 4;
EMERGENCY = 5;
PUBLIC_TRANSPORT = 6;
}
enum SensorType {
GPS = 0;
ACCELEROMETER = 1;
GYROSCOPE = 2;
TEMPERATURE = 3;
FUEL_LEVEL = 4;
ENGINE_RPM = 5;
}graph TD
A[Vehicle GPS] --> B[Create Message]
B --> C[Add Metadata]
C --> D[Generate Nonce]
D --> E[Hash Message]
E --> F[Sign with ECDSA]
F --> G[Encrypt Sensitive Data]
G --> H[Send to RSU]
H --> I[RSU Validation]
I --> J[Certificate Check]
J --> K[Signature Verification]
K --> L[Decrypt Data]
L --> M[Trust Computation]
M --> N[Store + Forward]
N --> O[API Gateway]
O --> P[Rate Limiting]
P --> Q[Authentication]
Q --> R[Authorization]
R --> S[Processing]
S --> T[Database]
S --> U[Cache]
S --> V[Analytics]
S --> W[WebSocket]
W --> X[Frontend Update]
V --> Y[Dashboard Charts]
U --> Z[Real-time Data]
- Rust: 1.70+ with Cargo
- PostgreSQL: 14+ with TimescaleDB extension
- Redis: 6.2+ for caching
- RabbitMQ: 3.9+ for message queuing
- Node.js: 18+ for frontend development
- Docker: 20.10+ for containerization
- Kubernetes: 1.25+ for orchestration (optional)
# Clone repository
git clone https://github.com/your-org/geovan.git
cd geovan
# Start infrastructure services
docker-compose up -d postgres redis rabbitmq
# Run database migrations
cargo run --bin migrate
# Start backend services
cargo run --bin geovan-api &
cargo run --bin geovan-tracker &
cargo run --bin geovan-trust &
# Start frontend
cd frontend
npm install
npm start
# Access the application
open http://localhost:3000# Build production images
docker build -t geovan/backend:latest ./backend
docker build -t geovan/frontend:latest ./frontend
# Deploy to Kubernetes
kubectl apply -f k8s/namespace.yaml
kubectl apply -f k8s/secrets.yaml
kubectl apply -f k8s/configmaps.yaml
kubectl apply -f k8s/deployments.yaml
kubectl apply -f k8s/services.yaml
kubectl apply -f k8s/ingress.yaml
# Scale services
kubectl scale deployment geovan-tracker --replicas=5
kubectl scale deployment geovan-trust --replicas=3# Database Configuration
DATABASE_URL=postgresql://user:pass@localhost:5432/geovan
REDIS_URL=redis://localhost:6379
RABBITMQ_URL=amqp://localhost:5672
# Security Configuration
JWT_SECRET=your-super-secret-jwt-key
CERTIFICATE_AUTHORITY_PATH=/etc/ssl/certs/ca-bundle.crt
ENCRYPTION_KEY=your-32-byte-encryption-key
# Performance Configuration
WORKER_THREADS=8
MAX_CONNECTIONS=1000
CACHE_TTL=300
RATE_LIMIT=1000
# Monitoring Configuration
PROMETHEUS_PORT=9090
GRAFANA_PORT=3000
LOG_LEVEL=info# config/security.toml
[authentication]
jwt_expiry = "24h"
refresh_token_expiry = "7d"
max_login_attempts = 5
lockout_duration = "15m"
[certificates]
ca_bundle_path = "/etc/ssl/certs/ca-bundle.crt"
cert_expiry_warning = "30d"
revocation_check_interval = "1h"
[encryption]
algorithm = "AES-256-GCM"
key_rotation_interval = "24h"
encrypted_fields = ["position", "metadata", "sensors"]
[privacy]
pseudonym_rotation_interval = "5m"
location_noise_stddev = 5.0
data_retention_days = 90
anonymization_enabled = true- System Performance: Response time, throughput, error rates
- Security Metrics: Failed authentications, suspicious activities
- Vehicle Analytics: Movement patterns, traffic density, speed analysis
- Trust Metrics: Average trust scores, anomaly detection rates
- Infrastructure: CPU, memory, disk, network utilization
- Real-time Map: Live vehicle positions with trust indicators
- Analytics Dashboard: Traffic patterns, security events, performance metrics
- Alert Management: Security alerts, system notifications, vehicle warnings
- User Management: Role-based access control, audit logs
- System Health: Service status, resource utilization, error rates
# Run all tests
cargo test
# Run specific test categories
cargo test --test security
cargo test --test performance
cargo test --test integration
# Run with coverage
cargo tarpaulin --out Html
# Performance benchmarks
cargo bench
# Security audit
cargo audit# Code formatting
cargo fmt
# Linting
cargo clippy
# Dependency updates
cargo update
# Documentation
cargo doc --open- Message Tampering: Mitigated by cryptographic signatures
- Replay Attacks: Prevented by sequence numbers and timestamps
- Sybil Attacks: Deterred by certificate validation and trust scoring
- Privacy Violations: Addressed by pseudonym rotation and encryption
- Denial of Service: Mitigated by rate limiting and load balancing
- GDPR: Data protection and privacy compliance
- CCPA: California consumer privacy compliance
- ISO 27001: Information security management
- SOC 2: Security, availability, and confidentiality
- NIST Cybersecurity Framework: Risk management framework
- ✅ Rust backend with security features
- ✅ React frontend with real-time updates
- ✅ Basic trust scoring and anomaly detection
- ✅ Docker containerization
- 🔄 Zero-knowledge proofs for privacy
- 🔄 Advanced threat intelligence
- 🔄 Behavioral analysis with ML
- 🔄 Certificate authority management
- 🔄 Kubernetes orchestration
- 🔄 Multi-region deployment
- 🔄 Advanced load balancing
- 🔄 Performance optimization
- 🔄 AI-powered traffic prediction
- 🔄 Advanced analytics dashboard
- 🔄 Mobile applications
- 🔄 Third-party integrations
We welcome contributions! Please see our Contributing Guide for details.
# Fork and clone
git clone https://github.com/your-username/geovan.git
cd geovan
# Install pre-commit hooks
pre-commit install
# Run development environment
docker-compose -f docker-compose.dev.yml up -d
cargo run --bin geovan-api- Rust: Follow Rust coding standards and use
cargo fmt - TypeScript: Use ESLint and Prettier for formatting
- Documentation: Include comprehensive docstrings and examples
- Testing: Maintain >90% test coverage
- Security: Follow OWASP security guidelines
This project is licensed under the MIT License - see the LICENSE file for details.
- Rust Community: For the excellent ecosystem and tooling
- React Team: For the powerful frontend framework
- OpenStreetMap: For map data and tiles
- Security Researchers: For vulnerability research and disclosure
- Documentation: docs.geovan.dev
- Discord: Join our community
- GitHub Issues: Report bugs
- Security: security@geovan.dev
GeoVAN - Building the future of secure, scalable, and intelligent vehicular networks. 🚗🔐⚡
Last updated: January 2024