An ever-increasing number of autonomous vehicles use bandwidth-greedy sensors such as cameras and LiDARs to sense and act to the world around us. Unfortunately, signal transmission in vehicles is vulnerable to passive and active cyber-physical attacks that may result in loss of intellectual property, or worse yet, the loss of control of a vehicle, potentially causing great harm. Therefore, it is important to investigate efficient cryptographic methods to secure signal transmission in such vehicles against outside threats. This study is motivated by the observation that previous publications have suggested legacy algorithms, which are either inefficient or insecure for vision-based signals. We show how stream ciphers and authenticated encryption can be applied to transfer sensor data securely and efficiently between computing devices suitable for distributed guidance, navigation, and control systems. We provide an efficient and flexible pipeline of cryptographic operations on image and point cloud data in the Robot Operating System (ROS). We also demonstrate how image data can be compressed to reduce the amount of data to be encrypted, transmitted, and decrypted. Experiments on embedded computers verify that modern software cryptographic algorithms perform very well on large sensor data. Hence, the introduction of such algorithms should enhance security without significantly compromising the overall performance.

越来越多的自动驾驶汽车使用摄像头和激光雷达等带宽贪婪的传感器来感知我们周围的世界并采取行动。不幸的是，车辆中的信号传输容易受到被动和主动的网络物理攻击，这可能会导致知识产权的损失，或者更糟的是，车辆失去控制，可能造成巨大的伤害。因此，研究有效的加密方法以保护此类车辆中的信号传输免受外部威胁非常重要。这项研究的动机是观察到以前的出版物提出了传统算法，这些算法对于基于视觉的信号要么效率低下要么不安全。我们展示了如何应用流密码和经过身份验证的加密在适用于分布式引导、导航和控制系统的计算设备之间安全有效地传输传感器数据。我们为机器人操作系统 (ROS) 中的图像和点云数据提供了高效且灵活的加密操作管道。我们还演示了如何压缩图像数据以减少要加密、传输和解密的数据量。在嵌入式计算机上的实验验证了现代软件加密算法在大型传感器数据上的表现非常好。因此，此类算法的引入应在不显着影响整体性能的情况下增强安全性。我们为机器人操作系统 (ROS) 中的图像和点云数据提供了高效且灵活的加密操作管道。我们还演示了如何压缩图像数据以减少要加密、传输和解密的数据量。在嵌入式计算机上的实验验证了现代软件加密算法在大型传感器数据上的表现非常好。因此，此类算法的引入应该可以在不显着影响整体性能的情况下增强安全性。我们为机器人操作系统 (ROS) 中的图像和点云数据提供了高效且灵活的加密操作管道。我们还演示了如何压缩图像数据以减少要加密、传输和解密的数据量。在嵌入式计算机上的实验验证了现代软件加密算法在大型传感器数据上的表现非常好。因此，此类算法的引入应在不显着影响整体性能的情况下增强安全性。