#!/usr/bin/env python3
"""
Approach 2: Statistical Analysis

Source: Chapter_13_Data_Provenance_and_Supply_Chain_Security
Category: supply_chain
"""

import argparse
import sys

# Analyze model behavior across many inputs
# Look for anomalous patterns
# - Specific inputs always produce same unusual output
# - Performance degradation on certain input types
# - Unexpected confidence scores

def backdoor_detection_test(model, test_dataset):
    results = []
    for input_data in test_dataset:
        output = model(input_data)
        # Statistical analysis
        results.append({
            'input': input_data,
            'output': output,
            'confidence': output.confidence,
            'latency': measure_latency(model, input_data)
        })

    # Detect anomalies
    anomalies = detect_outliers(results)
    return anomalies


def main():
    """Command-line interface."""
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("--verbose", "-v", action="store_true", help="Verbose output")
    args = parser.parse_args()
    
    # TODO: Add main execution logic
    pass

if __name__ == "__main__":
    main()