Hardware Acceleration Security

This document outlines security considerations and best practices for the hardware acceleration features implemented in Anya Bitcoin.

Overview

Hardware acceleration significantly improves performance for cryptographic operations, particularly for Taproot and batch verification. This document focuses on maintaining security while leveraging performance benefits.

Supported Hardware Acceleration

1. CPU Vectorization

  • AVX2/AVX512 instruction sets
  • SIMD operations for batch signature verification
  • Specialized cryptographic instruction sets (AES-NI, SHA-NI)

2. GPU Acceleration

  • CUDA for NVIDIA GPUs
  • OpenCL for cross-platform support
  • Batch operations for signature verification and hash computations

3. Neural Processing Units (NPUs)

  • AI accelerator optimizations for pattern recognition
  • Anomaly detection in transaction patterns
  • Hardware-accelerated validation of complex scripts

Security Considerations

1. Side-Channel Attack Prevention

Side-channel attacks exploit hardware-level information leakage (timing, power consumption, electromagnetic emissions) to extract sensitive data.

Mitigations

  • Constant-time operations for sensitive cryptographic functions
  • Blinding techniques for private key operations
  • Secure memory management with protections against cold boot attacks
  • Hardware-level countermeasures against power analysis
// Example of time-constant comparison with hardware acceleration
fn secure_compare(a: &[u8], b: &[u8]) -> bool {
    if a.len() != b.len() {
        return false;
    }

    // Use hardware acceleration if available with constant-time guarantees
    if hardware_support::has_secure_compare() {
        return hardware_support::secure_compare(a, b);
    }

    // Software fallback with constant-time comparison
    let mut result = 0u8;
    for (x, y) in a.iter().zip(b.iter()) {
        result |= x ^ y;
    }

    result == 0
}

2. Hardware Acceleration Fallbacks

Security Issues

  • Hardware implementations may contain bugs or vulnerabilities
  • Different hardware may produce inconsistent results
  • Hardware availability varies across environments

Mitigations

  • Always implement secure software fallbacks
  • Validate hardware results against software implementations for critical operations
  • Comprehensive testing across different hardware configurations
  • Version detection for hardware-specific vulnerabilities

3. Memory Management

Security Issues

  • GPU memory is not automatically cleared after computation
  • Shared memory environments in cloud deployments
  • DMA attacks on physical hardware

Mitigations

  • Explicit memory sanitization after sensitive operations
  • Encryption of data transferred to acceleration hardware
  • Memory isolation techniques for sensitive operations
  • Prevention of swap file usage for sensitive data

Implementation Security Guidelines

1. Batch Operations Security

// Example of secure batch verification
fn verify_batch_signatures(
    keys: &[XOnlyPublicKey],
    messages: &[&[u8]],
    signatures: &[SchnorrSignature],
) -> Result<bool, Error> {
    // Input validation
    if keys.len() != messages.len() || keys.len() != signatures.len() {
        return Err(Error::InvalidInput("Mismatched batch verification inputs"));
    }

    // Use hardware acceleration when available
    if hardware_support::has_batch_verification() {
        let hw_result = hardware_support::verify_batch(keys, messages, signatures);

        // Validate a random subset against software implementation (defense in depth)
        if hw_result && security_level == SecurityLevel::Critical {
            validate_random_subset(keys, messages, signatures)?;
        }

        return Ok(hw_result);
    }

    // Software fallback
    software_batch_verification(keys, messages, signatures)
}

2. Cryptographic Hardware Validation

  • Verify correct behavior with test vectors
  • Implement cryptographic integrity checks for hardware operations
  • Employ runtime verification techniques
  • Use differential fuzzing to detect inconsistencies

3. Error Handling

  • Secure failure modes for hardware acceleration errors
  • No sensitive information in error messages
  • Fallback mechanisms for hardware failures
  • Monitoring and alerting for hardware anomalies

Threat Model for Hardware Acceleration

Primary Threats

  1. Hardware Backdoors
  2. Mitigation: Validation against known-good software implementations

  3. Periodic security audits of hardware implementations

  4. Side-Channel Information Leakage

  5. Mitigation: Side-channel resistant implementations

  6. Regular testing with power analysis tools

  7. Inconsistent Results

  8. Mitigation: Verification of critical results

  9. Robust error handling with secure fallbacks

  10. Hardware Availability Attacks

  11. Mitigation: Graceful degradation to software implementations
  12. Resource limiting to prevent exhaustion attacks

Performance vs. Security Tradeoffs

Security-Critical Operations

For security-critical operations (e.g., signing with high-value keys):

  • Always prioritize security over performance
  • Use hardware acceleration only after thorough validation
  • Consider hardware security modules (HSMs) instead of general-purpose accelerators

Performance-Critical Operations

For performance-critical operations (e.g., batch verification of signatures):

  • Use hardware acceleration with appropriate safeguards
  • Implement periodic validation of hardware results
  • Balance security checks with performance considerations

Testing Requirements

  1. Functional Testing
  2. Test vectors for all cryptographic operations

  3. Cross-implementation verification

  4. Security Testing

  5. Side-channel analysis
  6. Differential fuzzing

  7. Incorrect input handling

  8. Performance Testing

  9. Load testing under various conditions
  10. Resource consumption monitoring
  11. Fallback performance measurement

Last updated: 2025-05-01