SaaS 行业观察：量子计算时代的网络安全挑战与应对

# 传统 RSA 加密（2048 位）
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography.hazmat.primitives import serialization

# 生成 RSA 密钥对
private_key = rsa.generate_private_key(
    public_exponent=65537,
    key_size=2048
)
public_key = private_key.public_key()

# 量子威胁：Shor 算法可以在多项式时间内分解大整数
# 经典计算机：需要 2^112 次操作（不可行）
# 量子计算机（4000 逻辑量子比特）：需要约 10^7 次操作（可行）

class ShorAlgorithmSimulation:
    def __init__(self, n_qubits):
        self.n_qubits = n_qubits
    
    def factor_large_number(self, N):
        """
        Shor 算法模拟：分解大整数 N
        时间复杂度：O((log N)^3)
        """
        # 量子傅里叶变换
        # 周期查找
        # 经典后处理
        
        # 返回 N 的因子
        factors = self.quantum_period_finding(N)
        return factors
    
    def break_rsa_2048(self):
        """
        破解 2048 位 RSA
        需要约 4000 个逻辑量子比特
        """
        N = 2**2048  # 简化表示
        
        # 量子计算分解
        p, q = self.factor_large_number(N)
        
        # 计算私钥
        phi = (p - 1) * (q - 1)
        d = modular_inverse(65537, phi)
        
        return {
            'p': p,
            'q': q,
            'private_exponent': d,
            'status': 'RSA-2048 broken'
        }

# 椭圆曲线加密（ECC）
from cryptography.hazmat.primitives.asymmetric import ec

# 生成 ECC 密钥对（P-256 曲线）
private_key = ec.generate_private_key(ec.SECP256R1())
public_key = private_key.public_key()

# 量子威胁：Shor 算法同样可以解决离散对数问题
# ECC-256 需要约 2500 个逻辑量子比特即可破解

class QuantumECCAttack:
    def __init__(self):
        self.curve = ec.SECP256R1()
    
    def solve_ecdlp(self, public_point, base_point):
        """
        解决椭圆曲线离散对数问题（ECDLP）
        找到 k 使得：public_point = k * base_point
        """
        # 量子算法步骤：
        # 1. 准备叠加态
        # 2. 应用椭圆曲线标量乘法
        # 3. 量子傅里叶变换
        # 4. 测量得到周期
        
        k = self.quantum_period_finding(public_point, base_point)
        return k
    
    def break_ecc_256(self, public_key):
        """
        破解 ECC-256
        需要约 2500 个逻辑量子比特
        """
        # 提取公钥点
        public_point = public_key.public_numbers()
        base_point = self.curve.generator
        
        # 量子计算私钥
        private_scalar = self.solve_ecdlp(public_point, base_point)
        
        return {
            'private_key': private_scalar,
            'status': 'ECC-256 broken'
        }

from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes

# AES-256 加密
key = b'0123456789abcdef0123456789abcdef'  # 256 位密钥
cipher = Cipher(algorithms.AES(key), modes.GCM(iv))

# 量子威胁：Grover 算法可以将搜索空间开平方
# AES-128：经典 2^128 → 量子 2^64（不安全）
# AES-256：经典 2^256 → 量子 2^128（仍然安全，但削弱）

class GroverAlgorithmSimulation:
    def __init__(self, n_qubits):
        self.n_qubits = n_qubits
    
    def search_key(self, ciphertext, plaintext, key_size):
        """
        Grover 算法：在无序数据库中搜索
        时间复杂度：O(sqrt(N))，其中 N = 2^key_size
        """
        # 量子步骤：
        # 1. 初始化均匀叠加态
        # 2. 应用 Oracle（检查密钥是否正确）
        # 3. 应用扩散算子
        # 4. 重复 sqrt(N) 次
        
        iterations = int(2 ** (key_size / 2))
        
        for i in range(iterations):
            # 量子迭代
            self.apply_oracle(ciphertext, plaintext)
            self.apply_diffusion()
        
        # 测量得到密钥
        key = self.measure()
        return key
    
    def attack_aes_128(self, ciphertext, plaintext):
        """
        攻击 AES-128
        需要约 2^64 次量子操作（可行）
        """
        key = self.search_key(ciphertext, plaintext, key_size=128)
        return {
            'key': key,
            'operations': 2**64,
            'status': 'AES-128 broken'
        }
    
    def attack_aes_256(self, ciphertext, plaintext):
        """
        攻击 AES-256
        需要约 2^128 次量子操作（仍然不可行）
        """
        key = self.search_key(ciphertext, plaintext, key_size=256)
        return {
            'key': key,
            'operations': 2**128,
            'status': 'AES-256 weakened but not broken'
        }

class HarvestNowDecryptLater:
    def __init__(self):
        self.intercepted_data = []
        self.metadata = []
    
    def intercept_encrypted_traffic(self, target):
        """
        阶段 1：收集加密数据（现在）
        """
        # 监听网络流量
        encrypted_packets = self.sniff_network(target)
        
        for packet in encrypted_packets:
            # 存储加密数据
            self.intercepted_data.append({
                'ciphertext': packet.payload,
                'timestamp': packet.timestamp,
                'source': packet.source,
                'destination': packet.destination,
                'protocol': packet.protocol,
                'encryption': packet.encryption_algorithm
            })
        
        return len(encrypted_packets)
    
    def store_for_future_decryption(self):
        """
        阶段 2：长期存储（等待量子计算机）
        """
        # 压缩并存储
        for data in self.intercepted_data:
            # 使用高效压缩
            compressed = compress(data['ciphertext'])
            
            # 存储到冷存储（成本低）
            cold_storage.archive(
                data=compressed,
                metadata=data,
                retention_years=20  # 保留 20 年
            )
        
        return {
            'total_data': len(self.intercepted_data),
            'storage_cost': self.calculate_storage_cost(),
            'expected_decrypt_year': 2030  # 预计量子计算机成熟年份
        }
    
    def decrypt_with_quantum_computer(self, year=2030):
        """
        阶段 3：使用量子计算机解密（未来）
        """
        if not self.quantum_computer_available():
            return {'status': 'waiting', 'year': year}
        
        decrypted_data = []
        
        for data in self.intercepted_data:
            encryption = data['encryption']
            
            if encryption in ['RSA-2048', 'ECC-256']:
                # 使用 Shor 算法破解
                private_key = self.shor_algorithm.break_encryption(data)
                
                # 解密数据
                plaintext = decrypt(data['ciphertext'], private_key)
                decrypted_data.append({
                    'plaintext': plaintext,
                    'original_metadata': data
                })
            
            elif encryption == 'AES-128':
                # 使用 Grover 算法破解
                key = self.grover_algorithm.attack_aes_128(
                    data['ciphertext'],
                    known_plaintext=None
                )
                
                plaintext = decrypt_aes(data['ciphertext'], key)
                decrypted_data.append({
                    'plaintext': plaintext,
                    'original_metadata': data
                })
        
        return {
            'status': 'success',
            'decrypted_count': len(decrypted_data),
            'sensitive_data_exposed': self.analyze_sensitivity(decrypted_data)
        }

import numpy as np
from numpy.polynomial import polynomial as P

class CrystalsKyber:
    """
    CRYSTALS-Kyber：基于格的后量子密钥封装机制
    NIST PQC 标准化竞赛获胜者
    安全性基于 Learning With Errors (LWE) 问题
    """
    
    def __init__(self, security_level=3):
        # Kyber-768（安全级别 3，相当于 AES-192）
        self.n = 256  # 多项式环维度
        self.k = 3    # 模块维度
        self.q = 3329 # 模数
        
        # 安全级别参数
        self.params = {
            1: {'k': 2, 'eta1': 3, 'eta2': 2},  # Kyber-512
            3: {'k': 3, 'eta1': 2, 'eta2': 2},  # Kyber-768
            5: {'k': 4, 'eta1': 2, 'eta2': 2}   # Kyber-1024
        }[security_level]
    
    def key_generation(self):
        """
        生成公私钥对
        """
        # 生成随机矩阵 A
        A = self.sample_matrix(self.k, self.k)
        
        # 生成秘密向量 s
        s = self.sample_vector(self.k, eta=self.params['eta1'])
        
        # 生成误差向量 e
        e = self.sample_vector(self.k, eta=self.params['eta1'])
        
        # 计算公钥：t = A*s + e
        t = self.matrix_vector_mult(A, s)
        t = self.vector_add(t, e)
        t = self.vector_mod(t, self.q)
        
        # 公钥和私钥
        public_key = (t, A)
        secret_key = s
        
        return {
            'public_key': public_key,
            'secret_key': secret_key,
            'security_level': 'quantum-resistant'
        }
    
    def encapsulate(self, public_key):
        """
        密钥封装：生成共享密钥
        """
        t, A = public_key
        
        # 生成随机向量 r
        r = self.sample_vector(self.k, eta=self.params['eta2'])
        
        # 生成误差向量 e1, e2
        e1 = self.sample_vector(self.k, eta=self.params['eta2'])
        e2 = self.sample_polynomial(eta=self.params['eta2'])
        
        # 计算密文：u = A^T*r + e1
        u = self.matrix_vector_mult(self.matrix_transpose(A), r)
        u = self.vector_add(u, e1)
        u = self.vector_mod(u, self.q)
        
        # 计算：v = t^T*r + e2 + message
        v = self.vector_inner_product(t, r)
        v = self.poly_add(v, e2)
        
        # 生成共享密钥
        shared_secret = self.hash_to_key(u, v)
        
        ciphertext = (u, v)
        
        return {
            'ciphertext': ciphertext,
            'shared_secret': shared_secret
        }
    
    def decapsulate(self, ciphertext, secret_key):
        """
        密钥解封装：恢复共享密钥
        """
        u, v = ciphertext
        s = secret_key
        
        # 计算：v - s^T*u
        message_noisy = self.poly_sub(
            v,
            self.vector_inner_product(s, u)
        )
        
        # 解码消息
        message = self.decode_message(message_noisy)
        
        # 恢复共享密钥
        shared_secret = self.hash_to_key(u, v)
        
        return shared_secret
    
    def sample_matrix(self, k1, k2):
        """
        从均匀分布采样矩阵
        """
        matrix = []
        for i in range(k1):
            row = []
            for j in range(k2):
                poly = self.sample_polynomial_uniform()
                row.append(poly)
            matrix.append(row)
        return matrix
    
    def sample_vector(self, k, eta):
        """
        从中心二项分布采样向量
        """
        vector = []
        for i in range(k):
            poly = self.sample_polynomial(eta=eta)
            vector.append(poly)
        return vector

class CrystalsDilithium:
    """
    CRYSTALS-Dilithium：基于格的后量子数字签名
    NIST PQC 标准化竞赛获胜者
    """
    
    def __init__(self, security_level=3):
        self.n = 256
        self.q = 8380417
        
        # Dilithium 参数
        self.params = {
            2: {'k': 4, 'l': 4, 'eta': 2},   # Dilithium-2
            3: {'k': 6, 'l': 5, 'eta': 4},   # Dilithium-3
            5: {'k': 8, 'l': 7, 'eta': 2}    # Dilithium-5
        }[security_level]
    
    def key_generation(self):
        """
        生成签名密钥对
        """
        # 生成随机种子
        rho = self.sample_random_bytes(32)
        
        # 生成矩阵 A
        A = self.expand_matrix_A(rho)
        
        # 生成秘密向量 s1, s2
        s1 = self.sample_vector(self.params['l'], eta=self.params['eta'])
        s2 = self.sample_vector(self.params['k'], eta=self.params['eta'])
        
        # 计算公钥：t = A*s1 + s2
        t = self.matrix_vector_mult(A, s1)
        t = self.vector_add(t, s2)
        
        # 公钥和私钥
        public_key = (rho, t)
        secret_key = (rho, s1, s2, t)
        
        return {
            'public_key': public_key,
            'secret_key': secret_key
        }
    
    def sign(self, message, secret_key):
        """
        生成数字签名
        """
        rho, s1, s2, t = secret_key
        A = self.expand_matrix_A(rho)
        
        # 随机化签名过程（防止侧信道攻击）
        while True:
            # 生成随机向量 y
            y = self.sample_vector(self.params['l'], eta=2**16)
            
            # 计算：w = A*y
            w = self.matrix_vector_mult(A, y)
            
            # 提取高位
            w1 = self.high_bits(w)
            
            # 计算挑战
            c = self.hash_to_challenge(rho, w1, message)
            
            # 计算签名：z = y + c*s1
            z = self.vector_add(y, self.vector_scalar_mult(c, s1))
            
            # 检查签名是否满足条件
            if self.check_signature_bounds(z, c, s2):
                break
        
        signature = (z, c)
        return signature
    
    def verify(self, message, signature, public_key):
        """
        验证数字签名
        """
        rho, t = public_key
        z, c = signature
        
        A = self.expand_matrix_A(rho)
        
        # 计算：w' = A*z - c*t
        Az = self.matrix_vector_mult(A, z)
        ct = self.vector_scalar_mult(c, t)
        w_prime = self.vector_sub(Az, ct)
        
        # 提取高位
        w1_prime = self.high_bits(w_prime)
        
        # 重新计算挑战
        c_prime = self.hash_to_challenge(rho, w1_prime, message)
        
        # 验证挑战是否匹配
        return c == c_prime

class SPHINCSPlus:
    """
    SPHINCS+：基于哈希的后量子数字签名
    安全性仅依赖于哈希函数的安全性
    """
    
    def __init__(self, security_level=3):
        # SPHINCS+ 参数
        self.params = {
            1: {'n': 16, 'h': 63, 'd': 7},   # SPHINCS+-128s
            3: {'n': 24, 'h': 64, 'd': 8},   # SPHINCS+-192s
            5: {'n': 32, 'h': 64, 'd': 8}    # SPHINCS+-256s
        }[security_level]
        
        self.n = self.params['n']  # 哈希输出长度
        self.h = self.params['h']  # 超树高度
        self.d = self.params['d']  # 超树层数
    
    def key_generation(self):
        """
        生成密钥对
        """
        # 生成随机种子
        seed = self.sample_random_bytes(self.n)
        
        # 生成根节点
        root = self.compute_merkle_tree_root(seed)
        
        public_key = root
        secret_key = seed
        
        return {
            'public_key': public_key,
            'secret_key': secret_key
        }
    
    def sign(self, message, secret_key):
        """
        生成签名（无状态，无需跟踪已使用的叶子）
        """
        seed = secret_key
        
        # 随机选择叶子节点
        leaf_index = self.sample_random_index()
        
        # 计算认证路径
        auth_path = self.compute_authentication_path(seed, leaf_index)
        
        # 生成 WOTS+ 签名
        wots_sig = self.wots_sign(message, seed, leaf_index)
        
        # 生成 FORS 签名（森林签名）
        fors_sig = self.fors_sign(message, seed, leaf_index)
        
        signature = {
            'leaf_index': leaf_index,
            'auth_path': auth_path,
            'wots_sig': wots_sig,
            'fors_sig': fors_sig
        }
        
        return signature
    
    def verify(self, message, signature, public_key):
        """
        验证签名
        """
        leaf_index = signature['leaf_index']
        auth_path = signature['auth_path']
        wots_sig = signature['wots_sig']
        fors_sig = signature['fors_sig']
        
        # 验证 FORS 签名
        if not self.fors_verify(message, fors_sig):
            return False
        
        # 验证 WOTS+ 签名
        if not self.wots_verify(message, wots_sig):
            return False
        
        # 验证认证路径
        computed_root = self.compute_root_from_auth_path(
            leaf_index, auth_path, wots_sig
        )
        
        return computed_root == public_key

class HybridEncryption:
    """
    混合加密：同时使用传统和后量子算法
    确保即使一种算法被破解，数据仍然安全
    """
    
    def __init__(self):
        # 传统算法
        self.classical_kem = RSA_KEM(key_size=4096)
        self.classical_sig = ECDSA(curve='P-384')
        
        # 后量子算法
        self.pq_kem = CrystalsKyber(security_level=5)
        self.pq_sig = CrystalsDilithium(security_level=5)
    
    def hybrid_key_generation(self):
        """
        生成混合密钥对
        """
        # 生成传统密钥
        classical_keys = self.classical_kem.key_generation()
        
        # 生成后量子密钥
        pq_keys = self.pq_kem.key_generation()
        
        # 组合公钥
        public_key = {
            'classical': classical_keys['public_key'],
            'post_quantum': pq_keys['public_key']
        }
        
        # 组合私钥
        secret_key = {
            'classical': classical_keys['secret_key'],
            'post_quantum': pq_keys['secret_key']
        }
        
        return {
            'public_key': public_key,
            'secret_key': secret_key
        }
    
    def hybrid_encapsulate(self, public_key):
        """
        混合密钥封装
        """
        # 传统密钥封装
        classical_result = self.classical_kem.encapsulate(
            public_key['classical']
        )
        
        # 后量子密钥封装
        pq_result = self.pq_kem.encapsulate(
            public_key['post_quantum']
        )
        
        # 组合共享密钥（使用密钥组合函数）
        combined_secret = self.combine_keys(
            classical_result['shared_secret'],
            pq_result['shared_secret']
        )
        
        ciphertext = {
            'classical': classical_result['ciphertext'],
            'post_quantum': pq_result['ciphertext']
        }
        
        return {
            'ciphertext': ciphertext,
            'shared_secret': combined_secret
        }
    
    def hybrid_decapsulate(self, ciphertext, secret_key):
        """
        混合密钥解封装
        """
        # 传统密钥解封装
        classical_secret = self.classical_kem.decapsulate(
            ciphertext['classical'],
            secret_key['classical']
        )
        
        # 后量子密钥解封装
        pq_secret = self.pq_kem.decapsulate(
            ciphertext['post_quantum'],
            secret_key['post_quantum']
        )
        
        # 组合共享密钥
        combined_secret = self.combine_keys(classical_secret, pq_secret)
        
        return combined_secret
    
    def combine_keys(self, key1, key2):
        """
        密钥组合函数
        使用 HKDF 或其他密钥派生函数
        """
        # 连接两个密钥
        combined = key1 + key2
        
        # 使用 HKDF 派生最终密钥
        final_key = hkdf(
            ikm=combined,
            salt=b'hybrid-encryption-v1',
            info=b'combined-shared-secret',
            length=32
        )
        
        return final_key
    
    def hybrid_sign(self, message, secret_key):
        """
        混合签名
        """
        # 传统签名
        classical_sig = self.classical_sig.sign(
            message,
            secret_key['classical']
        )
        
        # 后量子签名
        pq_sig = self.pq_sig.sign(
            message,
            secret_key['post_quantum']
        )
        
        signature = {
            'classical': classical_sig,
            'post_quantum': pq_sig
        }
        
        return signature
    
    def hybrid_verify(self, message, signature, public_key):
        """
        混合签名验证
        只有两个签名都有效，才认为签名有效
        """
        # 验证传统签名
        classical_valid = self.classical_sig.verify(
            message,
            signature['classical'],
            public_key['classical']
        )
        
        # 验证后量子签名
        pq_valid = self.pq_sig.verify(
            message,
            signature['post_quantum'],
            public_key['post_quantum']
        )
        
        return classical_valid and pq_valid

class CryptographicInventory:
    """
    加密资产清单：识别所有使用加密的位置
    """
    
    def __init__(self):
        self.inventory = {
            'tls_certificates': [],
            'api_keys': [],
            'database_encryption': [],
            'file_encryption': [],
            'authentication': [],
            'code_signing': []
        }
    
    def scan_infrastructure(self):
        """
        扫描基础设施，识别加密使用
        """
        # 扫描 TLS 证书
        self.scan_tls_certificates()
        
        # 扫描 API 密钥和令牌
        self.scan_api_keys()
        
        # 扫描数据库加密
        self.scan_database_encryption()
        
        # 扫描文件加密
        self.scan_file_encryption()
        
        # 扫描身份验证机制
        self.scan_authentication()
        
        # 扫描代码签名
        self.scan_code_signing()
        
        return self.generate_report()
    
    def scan_tls_certificates(self):
        """
        扫描 TLS 证书
        """
        certificates = []
        
        # 扫描所有域名和子域名
        for domain in self.get_all_domains():
            cert_info = self.inspect_certificate(domain)
            
            certificates.append({
                'domain': domain,
                'algorithm': cert_info['signature_algorithm'],
                'key_size': cert_info['key_size'],
                'issuer': cert_info['issuer'],
                'expiry': cert_info['expiry_date'],
                'quantum_vulnerable': self.is_quantum_vulnerable(cert_info)
            })
        
        self.inventory['tls_certificates'] = certificates
    
    def scan_database_encryption(self):
        """
        扫描数据库加密
        """
        databases = []
        
        for db in self.get_all_databases():
            encryption_info = self.inspect_database_encryption(db)
            
            databases.append({
                'database': db['name'],
                'type': db['type'],  # MySQL, PostgreSQL, etc.
                'encryption_at_rest': encryption_info['at_rest'],
                'encryption_in_transit': encryption_info['in_transit'],
                'key_management': encryption_info['key_management'],
                'quantum_vulnerable': self.is_quantum_vulnerable(encryption_info)
            })
        
        self.inventory['database_encryption'] = databases
    
    def is_quantum_vulnerable(self, crypto_info):
        """
        判断加密是否容易受到量子攻击
        """
        vulnerable_algorithms = [
            'RSA', 'DSA', 'ECDSA', 'ECDH',
            'DH', 'ElGamal'
        ]
        
        algorithm = crypto_info.get('algorithm', '')
        
        for vuln_alg in vulnerable_algorithms:
            if vuln_alg in algorithm:
                return True
        
        return False
    
    def generate_report(self):
        """
        生成量子脆弱性报告
        """
        total_items = sum(len(items) for items in self.inventory.values())
        vulnerable_items = self.count_vulnerable_items()
        
        report = {
            'total_cryptographic_assets': total_items,
            'quantum_vulnerable_assets': vulnerable_items,
            'vulnerability_percentage': (vulnerable_items / total_items) * 100,
            'breakdown': {
                category: {
                    'total': len(items),
                    'vulnerable': sum(1 for item in items 
                                    if item.get('quantum_vulnerable', False))
                }
                for category, items in self.inventory.items()
            },
            'recommendations': self.generate_recommendations()
        }
        
        return report
    
    def generate_recommendations(self):
        """
        生成迁移建议
        """
        recommendations = []
        
        # 高优先级：TLS 证书
        if self.inventory['tls_certificates']:
            vulnerable_certs = [c for c in self.inventory['tls_certificates']
                              if c['quantum_vulnerable']]
            if vulnerable_certs:
                recommendations.append({
                    'priority': 'high',
                    'category': 'TLS Certificates',
                    'action': 'Migrate to hybrid certificates with PQC',
                    'timeline': '6-12 months',
                    'affected_count': len(vulnerable_certs)
                })
        
        # 中优先级：数据库加密
        if self.inventory['database_encryption']:
            vulnerable_dbs = [d for d in self.inventory['database_encryption']
                            if d['quantum_vulnerable']]
            if vulnerable_dbs:
                recommendations.append({
                    'priority': 'medium',
                    'category': 'Database Encryption',
                    'action': 'Upgrade to PQC-compatible encryption',
                    'timeline': '12-18 months',
                    'affected_count': len(vulnerable_dbs)
                })
        
        return recommendations

class PQC_MigrationPlan:
    """
    后量子密码迁移计划
    """
    
    def __init__(self, inventory):
        self.inventory = inventory
        self.phases = []
    
    def create_migration_plan(self):
        """
        创建分阶段迁移计划
        """
        # 阶段 1：准备和评估（0-6 个月）
        phase1 = {
            'name': 'Preparation and Assessment',
            'duration': '0-6 months',
            'activities': [
                {
                    'task': 'Complete cryptographic inventory',
                    'owner': 'Security Team',
                    'deliverable': 'Inventory report'
                },
                {
                    'task': 'Risk assessment',
                    'owner': 'Risk Management',
                    'deliverable': 'Risk report'
                },
                {
                    'task': 'Vendor assessment',
                    'owner': 'Procurement',
                    'deliverable': 'Vendor capability matrix'
                },
                {
                    'task': 'Budget planning',
                    'owner': 'Finance',
                    'deliverable': 'Budget proposal'
                }
            ]
        }
        
        # 阶段 2：试点实施（6-12 个月）
        phase2 = {
            'name': 'Pilot Implementation',
            'duration': '6-12 months',
            'activities': [
                {
                    'task': 'Select pilot systems',
                    'owner': 'Architecture Team',
                    'deliverable': 'Pilot system list'
                },
                {
                    'task': 'Implement hybrid TLS',
                    'owner': 'Infrastructure Team',
                    'deliverable': 'Hybrid TLS deployment'
                },
                {
                    'task': 'Test PQC algorithms',
                    'owner': 'Security Team',
                    'deliverable': 'Test report'
                },
                {
                    'task': 'Performance benchmarking',
                    'owner': 'Performance Team',
                    'deliverable': 'Performance report'
                }
            ]
        }
        
        # 阶段 3：关键系统迁移（12-24 个月）
        phase3 = {
            'name': 'Critical Systems Migration',
            'duration': '12-24 months',
            'activities': [
                {
                    'task': 'Migrate TLS certificates',
                    'owner': 'Infrastructure Team',
                    'deliverable': 'Migrated certificates'
                },
                {
                    'task': 'Migrate API authentication',
                    'owner': 'API Team',
                    'deliverable': 'Migrated APIs'
                },
                {
                    'task': 'Migrate database encryption',
                    'owner': 'Database Team',
                    'deliverable': 'Migrated databases'
                },
                {
                    'task': 'Update client libraries',
                    'owner': 'SDK Team',
                    'deliverable': 'Updated SDKs'
                }
            ]
        }
        
        # 阶段 4：全面迁移（24-36 个月）
        phase4 = {
            'name': 'Full Migration',
            'duration': '24-36 months',
            'activities': [
                {
                    'task': 'Migrate remaining systems',
                    'owner': 'All Teams',
                    'deliverable': 'Fully migrated infrastructure'
                },
                {
                    'task': 'Deprecate legacy algorithms',
                    'owner': 'Security Team',
                    'deliverable': 'Deprecation notice'
                },
                {
                    'task': 'Security audit',
                    'owner': 'External Auditors',
                    'deliverable': 'Audit report'
                },
                {
                    'task': 'Documentation update',
                    'owner': 'Technical Writing',
                    'deliverable': 'Updated documentation'
                }
            ]
        }
        
        self.phases = [phase1, phase2, phase3, phase4]
        
        return self.phases
    
    def estimate_costs(self):
        """
        估算迁移成本
        """
        costs = {
            'phase1': {
                'personnel': 50000,   # 50K USD
                'tools': 20000,       # 20K USD
                'consulting': 30000,  # 30K USD
                'total': 100000       # 100K USD
            },
            'phase2': {
                'personnel': 150000,
                'tools': 50000,
                'testing': 30000,
                'total': 230000
            },
            'phase3': {
                'personnel': 400000,
                'infrastructure': 200000,
                'testing': 100000,
                'total': 700000
            },
            'phase4': {
                'personnel': 300000,
                'audit': 100000,
                'documentation': 50000,
                'total': 450000
            }
        }
        
        total_cost = sum(phase['total'] for phase in costs.values())
        
        return {
            'phase_costs': costs,
            'total_cost': total_cost,
            'roi': self.calculate_roi(total_cost)
        }
    
    def calculate_roi(self, total_cost):
        """
        计算投资回报率
        """
        # 避免的损失（量子攻击导致的损失）
        avoided_loss = 10000000  # 10M USD（估计）
        
        # 合规收益
        compliance_benefit = 500000  # 500K USD
        
        # 总收益
        total_benefit = avoided_loss + compliance_benefit
        
        # ROI
        roi = ((total_benefit - total_cost) / total_cost) * 100
        
        return {
            'avoided_loss': avoided_loss,
            'compliance_benefit': compliance_benefit,
            'total_benefit': total_benefit,
            'roi_percentage': roi
        }

class FinancialSaaSMigration:
    """
    金融 SaaS 平台的 PQC 迁移案例
    """
    
    def __init__(self):
        self.platform = 'FinTech Pro'
        self.users = 50000
        self.transactions_per_day = 1000000
    
    def implement_hybrid_tls(self):
        """
        实施混合 TLS
        """
        # 配置混合密钥交换
        tls_config = {
            'key_exchange': [
                'X25519',              # 传统 ECDH
                'Kyber768'            # 后量子 KEM
            ],
            'signature_algorithms': [
                'ECDSA_P256',          # 传统签名
                'Dilithium3'           # 后量子签名
            ],
            'cipher_suites': [
                'TLS_AES_256_GCM_SHA384'
            ]
        }
        
        # 部署到负载均衡器
        self.deploy_tls_config(tls_config)
        
        # 监控性能和兼容性
        metrics = self.monitor_tls_performance()
        
        return {
            'status': 'deployed',
            'performance_impact': metrics['latency_increase_ms'],
            'compatibility': metrics['client_compatibility_percentage']
        }
    
    def migrate_api_authentication(self):
        """
        迁移 API 身份验证
        """
        # 生成混合 API 密钥
        api_keys = []
        
        for client in self.get_all_api_clients():
            # 生成传统密钥
            classical_key = self.generate_classical_api_key()
            
            # 生成后量子密钥
            pq_key = self.generate_pq_api_key()
            
            # 组合密钥
            hybrid_key = {
                'classical': classical_key,
                'post_quantum': pq_key,
                'client_id': client['id']
            }
            
            api_keys.append(hybrid_key)
            
            # 通知客户端更新
            self.notify_client(client, hybrid_key)
        
        return {
            'migrated_clients': len(api_keys),
            'status': 'complete'
        }
    
    def upgrade_database_encryption(self):
        """
        升级数据库加密
        """
        # 迁移到后量子加密
        migration_plan = {
            'phase1': {
                'action': 'Enable hybrid encryption for new data',
                'duration': '2 weeks'
            },
            'phase2': {
                'action': 'Re-encrypt existing data',
                'duration': '4 weeks'
            },
            'phase3': {
                'action': 'Verify data integrity',
                'duration': '1 week'
            }
        }
        
        # 执行迁移
        for phase_name, phase in migration_plan.items():
            self.execute_migration_phase(phase)
        
        return {
            'status': 'complete',
            'databases_migrated': 15,
            'data_reencrypted': '500 TB'
        }