编辑代码

import numpy as np
import torch
import torch.nn as nn
from qiskit import QuantumCircuit, Aer, execute
from qiskit.circuit.library import TwoLocal
from hashlib import sha256
import random
from collections import defaultdict
import time

# 数据预处理模块
class DataPreprocessor:
    def __init__(self, num_qubits):
        self.num_qubits = num_qubits

    def encode_to_quantum_state(self, data):
        """将经典数据编码为量子态"""
        # 归一化数据
        normalized_data = data / np.linalg.norm(data)
        # 创建量子电路
        qc = QuantumCircuit(self.num_qubits)
        for i in range(self.num_qubits):
            qc.rx(normalized_data[i], i)  # 使用旋转门编码数据
        return qc

# 量子Transformer模块
class QuantumTransformer:
    def __init__(self, num_qubits):
        self.num_qubits = num_qubits
        self.backend = Aer.get_backend('statevector_simulator')

    def quantum_self_attention(self, qc):
        """量子自注意力机制"""
        # 使用CNOT门实现量子注意力
        for i in range(self.num_qubits - 1):
            qc.cx(i, i + 1)
        return qc

    def quantum_feedforward(self, qc):
        """量子前馈网络"""
        # 使用Hadamard门实现非线性变换
        for i in range(self.num_qubits):
            qc.h(i)
        return qc

    def measure_and_decode(self, qc):
        """量子测量与解码"""
        # 添加测量门
        qc.measure_all()
        # 执行量子电路
        result = execute(qc, self.backend, shots=1024).result()
        counts = result.get_counts(qc)
        # 解码为经典输出
        output = max(counts, key=counts.get)
        return int(output, 2) / (2 ** self.num_qubits)  # 归一化输出

# 信誉机制模块
class ReputationMechanism:
    def __init__(self, alpha=0.7):
        self.alpha = alpha  # 历史信誉值的权重

    def update_reputation(self, history_reputation, quantum_output):
        """更新信誉值"""
        return self.alpha * history_reputation + (1 - self.alpha) * quantum_output

# 身份验证模块(抵御Sybil攻击)
class IdentityVerification:
    def __init__(self):
        self.registered_nodes = set()  # 已注册的节点

    def register_node(self, node_id, public_key):
        """注册节点"""
        node_hash = sha256(public_key.encode()).hexdigest()
        if node_hash in self.registered_nodes:
            raise ValueError("节点已注册")
        self.registered_nodes.add(node_hash)
        print(f"节点 {node_id} 注册成功")

    def verify_node(self, node_id, public_key):
        """验证节点身份"""
        node_hash = sha256(public_key.encode()).hexdigest()
        if node_hash not in self.registered_nodes:
            raise ValueError("节点未注册或身份无效")
        print(f"节点 {node_id} 验证成功")
        return True

# Eclipse攻击防御模块
class EclipseDefense:
    def __init__(self, network_size):
        self.network_size = network_size

    def select_random_neighbors(self, node_id, num_neighbors=5):
        """随机选择邻居节点"""
        neighbors = random.sample(range(self.network_size), num_neighbors)
        print(f"节点 {node_id} 的随机邻居: {neighbors}")
        return neighbors

    def multi_path_communication(self, node_id, data):
        """多路径通信"""
        neighbors = self.select_random_neighbors(node_id)
        for neighbor in neighbors:
            print(f"通过邻居 {neighbor} 发送数据: {data}")

# DDoS攻击防御模块
class DDoSDefense:
    def __init__(self, rate_limit=10):
        self.rate_limit = rate_limit  # 每秒最大请求数
        self.request_counts = defaultdict(int)  # 记录每个节点的请求次数
        self.last_reset_time = time.time()

    def check_rate_limit(self, node_id):
        """检查速率限制"""
        current_time = time.time()
        if current_time - self.last_reset_time > 1:  # 每秒重置计数器
            self.request_counts.clear()
            self.last_reset_time = current_time
        self.request_counts[node_id] += 1
        if self.request_counts[node_id] > self.rate_limit:
            print(f"节点 {node_id} 触发速率限制,请求被拒绝")
            return False
        print(f"节点 {node_id} 请求通过")
        return True

    def filter_by_reputation(self, node_id, reputation):
        """根据信誉值过滤请求"""
        if reputation < 0.5:  # 假设信誉值低于0.5的节点为低信誉
            print(f"节点 {node_id} 信誉值过低,请求被拒绝")
            return False
        return True

# 主算法(整合安全机制)
class SecureQuantumTransformerReputation(QuantumTransformerReputation):
    def __init__(self, num_qubits, alpha=0.7, network_size=100):
        super().__init__(num_qubits, alpha)
        self.identity_verification = IdentityVerification()
        self.eclipse_defense = EclipseDefense(network_size)
        self.ddos_defense = DDoSDefense()

    def run_secure(self, node_id, public_key, data, history_reputation):
        """运行安全的信誉算法"""
        # 身份验证
        self.identity_verification.verify_node(node_id, public_key)
        # 速率限制检查
        if not self.ddos_defense.check_rate_limit(node_id):
            return None
        # 信誉过滤
        if not self.ddos_defense.filter_by_reputation(node_id, history_reputation):
            return None
        # 多路径通信
        self.eclipse_defense.multi_path_communication(node_id, data)
        # 运行量子Transformer算法
        return self.run(data, history_reputation)

# 测试
if __name__ == "__main__":
    # 示例数据
    data = np.array([0.5, 0.3, 0.8])  # 车辆行为数据
    history_reputation = 0.6  # 历史信誉值
    node_id = "vehicle_123"
    public_key = "public_key_123"
    network_size = 100  # 网络规模

    # 初始化安全算法
    num_qubits = 3  # 量子比特数
    secure_algorithm = SecureQuantumTransformerReputation(num_qubits, network_size=network_size)

    # 注册节点
    secure_algorithm.identity_verification.register_node(node_id, public_key)

    # 运行安全的信誉算法
    updated_reputation = secure_algorithm.run_secure(node_id, public_key, data, history_reputation)
    if updated_reputation is not None:
        print(f"更新后的信誉值: {updated_reputation}")