Distorting the adversary’s view: a CPS approach to privacy and security


This project develops a novel Cyber Physical System (CPS) centric-approach to privacy and security for wireless networked CPS systems, by reconciling the low-delay and low-jitter requirements of CPS applications with the requirements imposed by security and privacy. Our starting observation is that, in CPS, an adversary’s primary goal is not to learn all the raw data, but instead core attributes, such as the state or control actions that are derived from data. Building on this observation, we propose to use a distortion measure for security that maximizes the difference between the eavesdropper’s estimate and the true value of the function computing the attributes of interest, reducing the adversary’s ability to disrupt normal operation of CPS. We posit that we can protect these core attributes with fewer resources than needed to protect all the raw data. Ensuring secure and private information exchange over networked CPS systems is essential to building a thriving ecosystem of applications that range from autonomous cars and drones, to the Internet-of-Things (IoT), to immersive environments such as augmented reality for health, education, and collaboration. Our educational plan engages not only graduate students and postdocs but also high school and undergraduate students.

The project considers both passive and active attacks. We will quantify novel privacy and security measures for CPS systems that are based on distortion measurements in a metric space; we will develop fundamental bounds as well as low complexity and low overhead coding schemes; we will quantify the disruptive power of active adversaries and design pro-active and retro-active defense mechanisms. Our approach will offer an alternative to wireless network encryption methods, by designing for low-delay, low-jitter requirements of CPS.