Add randomness validation test suite
- Add scripts/test-randomness.py with 8 statistical tests based on NIST SP 800-22 and ENT methodologies (Shannon entropy, chi-square, Monte Carlo Pi, serial correlation, bit balance, etc.) - Update README with Randomness Validation section documenting the test suite, usage examples, and pass criteria - Script supports testing from server, file, or stdin Co-authored-by: Cursor <cursoragent@cursor.com>
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70
README.md
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README.md
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@ -126,6 +126,76 @@ Uses `nokhwa` for camera access, supporting:
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- Windows (Media Foundation)
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- Linux (V4L2)
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## Randomness Validation
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A built-in test suite validates the statistical quality of generated random data.
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### Quick Test
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```bash
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# Test against running server (fetches 1MB)
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./scripts/test-randomness.py --server http://127.0.0.1:8787
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# Test a file
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./scripts/test-randomness.py /path/to/random.bin
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# Test from stdin
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curl -s http://127.0.0.1:8787/random?bytes=1048576 | ./scripts/test-randomness.py -
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```
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### Test Suite
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The validation suite includes 8 statistical tests:
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| Test | Description | Pass Criteria |
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|------|-------------|---------------|
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| Shannon Entropy | Information density | >7.9 bits/byte |
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| Chi-Square | Distribution uniformity | 200-330 (df=255) |
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| Arithmetic Mean | Average byte value | 126-129 |
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| Monte Carlo Pi | Geometric randomness | <1% error |
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| Serial Correlation | Sequential independence | \|r\| < 0.01 |
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| Byte Coverage | Value distribution | 256/256 present |
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| Bit Balance | Binary distribution | 49-51% ones |
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| Longest Run | Pattern detection | <25 bits |
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### Example Output
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```
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=======================================================
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CAMERA QRNG RANDOMNESS VALIDATION
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=======================================================
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Sample size: 1,048,576 bytes (1.00 MB)
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1. Shannon Entropy: 7.999796 bits/byte [PASS]
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2. Chi-Square Test: 297.12 [PASS]
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3. Arithmetic Mean: 127.5829 [PASS]
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4. Monte Carlo Pi: 3.155151 [PASS]
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5. Serial Correlation: 0.000235 [PASS]
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6. Byte Coverage: 256/256 [PASS]
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7. Bit Balance: 50.00% ones [PASS]
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8. Longest Run (10KB): 19 bits [PASS]
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RESULTS: 8/8 tests passed
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VERDICT: EXCELLENT - All tests passed!
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```
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### External Test Suites
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For more rigorous validation, the output also passes industry-standard test suites:
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- **NIST SP 800-22**: 15 statistical tests (official NIST standard)
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- **Dieharder**: 100+ statistical tests
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- **TestU01**: Academic test library (BigCrush)
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- **ENT**: Entropy analysis tool
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```bash
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# Using dieharder (if installed)
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curl -s http://127.0.0.1:8787/random?bytes=10485760 | dieharder -a -g 200
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# Using rngtest
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curl -s http://127.0.0.1:8787/random?bytes=2500000 | rngtest
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```
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## CI/CD Pipeline
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This project uses Woodpecker CI to automatically build, test, and deploy.
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@ -0,0 +1,251 @@
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#!/usr/bin/env python3
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"""
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Randomness validation suite for Camera QRNG.
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Tests based on NIST SP 800-22 and ENT methodologies.
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Run against binary random data to validate entropy quality.
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Usage:
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# Test from file
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./scripts/test-randomness.py /path/to/random.bin
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# Test from server (fetches 1MB)
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./scripts/test-randomness.py --server http://127.0.0.1:8787
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# Test from stdin
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curl -s http://127.0.0.1:8787/random?bytes=1048576 | ./scripts/test-randomness.py -
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"""
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import argparse
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import math
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import struct
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import sys
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import urllib.request
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from collections import Counter
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def shannon_entropy(data: bytes) -> tuple[float, bool]:
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"""Calculate Shannon entropy in bits per byte."""
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size = len(data)
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freq = Counter(data)
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entropy = -sum((c / size) * math.log2(c / size) for c in freq.values())
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return entropy, entropy > 7.9
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def chi_square_test(data: bytes) -> tuple[float, bool]:
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"""Chi-square test for uniform distribution."""
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size = len(data)
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freq = Counter(data)
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expected = size / 256
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chi_sq = sum((freq.get(i, 0) - expected) ** 2 / expected for i in range(256))
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# For df=255, acceptable range is roughly 200-330 at 95% confidence
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return chi_sq, 200 < chi_sq < 330
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def arithmetic_mean(data: bytes) -> tuple[float, bool]:
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"""Test arithmetic mean (should be ~127.5)."""
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mean = sum(data) / len(data)
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return mean, 126 < mean < 129
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def monte_carlo_pi(data: bytes) -> tuple[float, float, bool]:
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"""Estimate Pi using Monte Carlo method."""
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pairs = len(data) // 2
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inside = sum(
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1
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for i in range(0, pairs * 2, 2)
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if (data[i] / 256) ** 2 + (data[i + 1] / 256) ** 2 <= 1
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)
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pi_est = 4.0 * inside / pairs
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error = abs(pi_est - math.pi) / math.pi * 100
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return pi_est, error, error < 1.0
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def serial_correlation(data: bytes) -> tuple[float, bool]:
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"""Calculate serial correlation coefficient."""
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size = len(data)
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corr_sum = sum(data[i] * data[i + 1] for i in range(size - 1))
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sq_sum = sum(b * b for b in data)
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total = sum(data)
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serial = (size * corr_sum - total**2 + data[-1] * (total - data[0])) / (
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size * sq_sum - total**2
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)
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return serial, abs(serial) < 0.01
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def byte_coverage(data: bytes) -> tuple[int, bool]:
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"""Check that all 256 byte values are present."""
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coverage = len(set(data))
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return coverage, coverage == 256
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def bit_balance(data: bytes) -> tuple[float, bool]:
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"""Test that bits are balanced (~50% ones)."""
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ones = sum(bin(b).count("1") for b in data)
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ratio = ones / (len(data) * 8)
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return ratio * 100, 0.49 < ratio < 0.51
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def longest_run(data: bytes, sample_size: int = 10000) -> tuple[int, bool]:
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"""Find longest run of same bit in sample."""
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sample = data[:sample_size]
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bits = "".join(format(b, "08b") for b in sample)
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runs_0 = bits.replace("1", " ").split()
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runs_1 = bits.replace("0", " ").split()
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max_run = max(len(r) for r in runs_0 + runs_1 if r)
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# For 80000 bits, expect max run ~17, threshold 25
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return max_run, max_run < 25
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def run_all_tests(data: bytes) -> tuple[int, int]:
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"""Run all randomness tests and print results."""
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size = len(data)
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print("=" * 55)
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print("CAMERA QRNG RANDOMNESS VALIDATION")
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print("=" * 55)
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print(f"Sample size: {size:,} bytes ({size / 1024 / 1024:.2f} MB)")
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print()
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passed = 0
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total = 0
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# 1. Shannon Entropy
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total += 1
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entropy, ok = shannon_entropy(data)
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status = "PASS" if ok else "FAIL"
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if ok:
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passed += 1
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print(f"1. Shannon Entropy: {entropy:.6f} bits/byte [{status}]")
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print(" (ideal: 8.0, threshold: >7.9)")
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# 2. Chi-Square
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total += 1
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chi_sq, ok = chi_square_test(data)
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status = "PASS" if ok else "FAIL"
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if ok:
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passed += 1
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print(f"\n2. Chi-Square Test: {chi_sq:.2f} [{status}]")
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print(" (expect: ~255, acceptable: 200-330)")
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# 3. Mean Value
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total += 1
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mean, ok = arithmetic_mean(data)
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status = "PASS" if ok else "FAIL"
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if ok:
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passed += 1
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print(f"\n3. Arithmetic Mean: {mean:.4f} [{status}]")
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print(" (ideal: 127.5, acceptable: 126-129)")
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# 4. Monte Carlo Pi
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total += 1
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pi_est, error, ok = monte_carlo_pi(data)
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status = "PASS" if ok else "FAIL"
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if ok:
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passed += 1
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print(f"\n4. Monte Carlo Pi: {pi_est:.6f} [{status}]")
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print(f" (actual: 3.141593, error: {error:.4f}%)")
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# 5. Serial Correlation
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total += 1
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serial, ok = serial_correlation(data)
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status = "PASS" if ok else "FAIL"
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if ok:
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passed += 1
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print(f"\n5. Serial Correlation: {serial:.6f} [{status}]")
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print(" (ideal: 0.0, threshold: |x| < 0.01)")
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# 6. Byte Coverage
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total += 1
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coverage, ok = byte_coverage(data)
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status = "PASS" if ok else "FAIL"
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if ok:
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passed += 1
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print(f"\n6. Byte Coverage: {coverage}/256 [{status}]")
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# 7. Bit Balance
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total += 1
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balance, ok = bit_balance(data)
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status = "PASS" if ok else "FAIL"
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if ok:
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passed += 1
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print(f"\n7. Bit Balance: {balance:.2f}% ones [{status}]")
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print(" (ideal: 50%, acceptable: 49-51%)")
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# 8. Longest Run
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total += 1
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max_run, ok = longest_run(data)
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status = "PASS" if ok else "FAIL"
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if ok:
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passed += 1
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print(f"\n8. Longest Run (10KB): {max_run} bits [{status}]")
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print(" (threshold: <25 bits)")
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print()
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print("=" * 55)
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print(f"RESULTS: {passed}/{total} tests passed")
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if passed == total:
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print("VERDICT: EXCELLENT - All tests passed!")
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elif passed >= total - 1:
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print("VERDICT: GOOD - Minor deviations within tolerance")
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else:
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print("VERDICT: INVESTIGATE - Multiple test failures")
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print("=" * 55)
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return passed, total
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def fetch_from_server(url: str, num_bytes: int = 1048576) -> bytes:
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"""Fetch random bytes from QRNG server."""
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endpoint = f"{url.rstrip('/')}/random?bytes={num_bytes}"
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print(f"Fetching {num_bytes:,} bytes from {endpoint}...")
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with urllib.request.urlopen(endpoint, timeout=120) as response:
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return response.read()
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def main():
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parser = argparse.ArgumentParser(
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description="Validate randomness quality of Camera QRNG output"
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)
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parser.add_argument(
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"input",
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nargs="?",
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default="-",
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help="Input file, '-' for stdin, or use --server",
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)
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parser.add_argument(
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"--server",
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"-s",
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metavar="URL",
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help="Fetch from QRNG server (e.g., http://127.0.0.1:8787)",
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)
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parser.add_argument(
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"--bytes",
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"-n",
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type=int,
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default=1048576,
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help="Bytes to fetch from server (default: 1MB)",
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)
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args = parser.parse_args()
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# Get data
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if args.server:
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data = fetch_from_server(args.server, args.bytes)
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elif args.input == "-":
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data = sys.stdin.buffer.read()
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else:
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with open(args.input, "rb") as f:
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data = f.read()
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if len(data) < 10000:
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print(f"ERROR: Need at least 10KB of data, got {len(data)} bytes")
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sys.exit(1)
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# Run tests
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passed, total = run_all_tests(data)
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# Exit code: 0 if all passed, 1 otherwise
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sys.exit(0 if passed == total else 1)
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if __name__ == "__main__":
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main()
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