As Cyber-Physical Systems (CPSs) employing mobile nodes continue to integrate into the physical world, ensuring their safety and security become crucial goals. Due to their mobility, real-time, energy and safety constraints, coupled by their reliance on communication mediums that are subject to interference and intentional jamming, the projected complexities in Mobile CPSs will far exceed those of traditional computing systems. Such increase in complexity widens the malicious opportunities for adversaries and with many components interacting together, distinguishing between normal and abnormal behaviors becomes quite challenging.
The research work in this project falls along two main thrusts: (1) identifying stealthy attacks and (2) developing defense mechanisms. Along the first thrust, a unifying theoretical framework is developed to uncover attacks in a systematic manner whereby an adversary solves Markovian Decision Processes problems to identify optimal and suboptimal attack policies. The effects of the attacks are assessed through different instantiations of damage and cost metrics. Along the second thrust, novel randomization controllers and randomization-aware anomaly detection mechanisms are developed to prevent, detect and mitigate stealthy attacks.
The outcomes of this CAREER project will ultimately provide concrete foundations to build more secure systems in the areas of robotics, autonomous vehicles, and intelligent transportation systems. The educational activities--as in curriculum development and hands-on laboratory experiences--will provide students with the essential skills to build dependable and trustworthy systems, while ensuring the participation of undergraduates, women and underrepresented minorities. The outreach activities will expose high school students to Computer Science education and scientific research.
