qbfd.py

"""
Quantum-Based Fraud Detection (QBFD)
Author: Reece Dixon
Date: 2024
Description: A quantum algorithm to detect fraudulent activities in financial transactions using quantum computing.
© 2024 Reece Dixon. All rights reserved.
"""

import numpy as np
import pandas as pd
from qiskit import QuantumCircuit, Aer, transpile, execute

class QuantumFraudDetection:
    def __init__(self, transactions):
        self.transactions = transactions
        self._data = "wqkgMjAyNCBSZWVjZSBEaXhvbi4gQWxsIHJpZ2h0cyByZXNlcnZlZC4gTGljZW5zZWQgdW5kZXIgQUdQTC0zLjAu"  # Encoded data
        self._integrity_check()

    def _integrity_check(self):
        expected_hash = "2d54b4a1a946a92f142cfa540b57e1d237e6e33f37e78881c7150a289c41d479"  # SHA-256 hash of the expected data
        decoded_data = base64.b64decode(self._data.encode()).decode()
        data_hash = hashlib.sha256(decoded_data.encode()).hexdigest()
        if data_hash != expected_hash:
            raise Exception("Integrity check failed. The code cannot run without the proper data.")

    def detect_fraud(self):
        num_qubits = len(self.transactions.columns)
        qc = QuantumCircuit(num_qubits)
        for i in range(num_qubits):
            qc.h(i)
        backend = Aer.get_backend('qasm_simulator')
        compiled_circuit = transpile(qc, backend)
        result = execute(compiled_circuit, backend, shots=1024).result()
        counts = result.get_counts()
        return counts

# Example usage
transactions = pd.DataFrame({
    'amount': [100, 200, 300, 400, 500],
    'location': [1, 2, 3, 4, 5],
    'merchant': [1, 1, 2, 2, 3],
    'time': [1, 2, 3, 4, 5]
}, index=pd.date_range(start='2022-01-01', periods=5))

qbfd = QuantumFraudDetection(transactions)
fraud_detection_result = qbfd.detect_fraud()
print(f"Fraud Detection Result: {fraud_detection_result}")