004_信息安全基础在具身AI中的应用：物理与数字融合的安全架构

# 鲁棒感知验证示例
class RobustPerceptionValidator:
    def __init__(self, sensor_config):
        self.sensor_config = sensor_config
        self.confidence_thresholds = {
            'camera': 0.85,
            'lidar': 0.90,
            'radar': 0.88,
            'imu': 0.92
        }
    
    def validate_perception(self, perception_data):
        """验证多模态感知数据的一致性和可靠性"""
        validation_results = {}
        cross_validation_passed = True
        
        # 1. 单模态数据有效性验证
        for sensor_type, data in perception_data.items():
            if sensor_type in self.confidence_thresholds:
                # 检查置信度
                if 'confidence' in data and data['confidence'] < self.confidence_thresholds[sensor_type]:
                    validation_results[sensor_type] = {
                        'valid': False,
                        'reason': f'Low confidence: {data["confidence"]}',
                        'recommendation': 'Use redundant sensors'
                    }
                    cross_validation_passed = False
                else:
                    validation_results[sensor_type] = {'valid': True}
        
        # 2. 多模态数据交叉验证
        if 'camera' in perception_data and 'lidar' in perception_data:
            if not self._cross_validate_camera_lidar(
                perception_data['camera'], 
                perception_data['lidar']
            ):
                validation_results['cross_validation'] = {
                    'valid': False,
                    'reason': 'Camera-LiDAR data inconsistency',
                    'recommendation': 'Prioritize LiDAR data'
                }
                cross_validation_passed = False
        
        # 3. 异常检测
        if cross_validation_passed:
            # 进一步检查是否存在对抗性模式
            if self._detect_adversarial_pattern(perception_data):
                validation_results['adversarial_detection'] = {
                    'detected': True,
                    'action': 'Activate robust perception mode'
                }
                cross_validation_passed = False
        
        return {
            'overall_valid': cross_validation_passed,
            'detailed_results': validation_results,
            'timestamp': self._get_current_timestamp()
        }
    
    def _cross_validate_camera_lidar(self, camera_data, lidar_data):
        # 实现摄像头和激光雷达数据的交叉验证逻辑
        pass
    
    def _detect_adversarial_pattern(self, perception_data):
        # 检测可能的对抗性模式
        pass

# 具身AI安全通信协议示例
class EmbodiedAISecureProtocol:
    def __init__(self, device_id, private_key_path, ca_cert_path):
        self.device_id = device_id
        self.private_key = self._load_private_key(private_key_path)
        self.ca_cert = self._load_ca_cert(ca_cert_path)
        self.tls_context = self._create_tls_context()
        self.message_counter = 0
        self.session_keys = {}
    
    def _load_private_key(self, key_path):
        # 加载设备私钥
        pass
    
    def _load_ca_cert(self, cert_path):
        # 加载CA证书
        pass
    
    def _create_tls_context(self):
        # 创建TLS上下文
        pass
    
    def establish_secure_channel(self, peer_id, peer_cert):
        # 建立与对等组件的安全通道
        # 1. 验证对等组件证书
        # 2. 执行密钥交换
        # 3. 生成会话密钥
        pass
    
    def send_message(self, peer_id, message_type, payload):
        # 发送安全消息
        # 1. 增加消息计数器
        # 2. 生成消息认证码(MAC)
        # 3. 加密消息
        # 4. 添加元数据和签名
        self.message_counter += 1
        message = {
            'device_id': self.device_id,
            'peer_id': peer_id,
            'type': message_type,
            'counter': self.message_counter,
            'timestamp': self._get_timestamp(),
            'payload': payload
        }
        
        # 加密和认证
        encrypted_message = self._encrypt_and_authenticate(message, peer_id)
        return encrypted_message
    
    def receive_message(self, encrypted_message):
        # 接收并验证消息
        # 1. 验证签名
        # 2. 解密消息
        # 3. 检查消息计数器（防重放）
        # 4. 验证消息完整性
        message = self._decrypt_and_verify(encrypted_message)
        
        # 检查消息计数器，防止重放攻击
        if not self._validate_counter(message['device_id'], message['counter']):
            raise SecurityException("Invalid message counter - possible replay attack")
        
        return message
    
    def _encrypt_and_authenticate(self, message, peer_id):
        # 加密消息并添加认证信息
        pass
    
    def _decrypt_and_verify(self, encrypted_message):
        # 解密消息并验证
        pass