Privacy and Resilience in Networked Robotic Systems



We are witnessing a profusion of networked robotic platforms with distinct features and unique capabilities. To exploit the diversity of such robotic networks, we are contriving ecosystems of tightly interconnected and interdependent heterogeneous entities. However, as connections are established, information is shared, and dependencies are created, these systems give rise to new vulnerabilities and threats.

I begin my talk by addressing the question of how heterogeneity affects the privacy of dynamic robot networks. With the ultimate goal of securing disruption-free operation, I introduce a model of differential privacy aimed at concealing critical robotic entities. Yet, even if we are able to protect individual robot roles, the hardware platforms may still be compromised. In light of this threat, my focus then shifts to the question of how to provide resilience in the face of non-cooperative and malicious agents. I show how precautionary connectivity management allows the robot networks to function, even in the presence of compromised individuals. Finally, I illustrate the effectiveness of this strategy on applications of vehicle flocking and perimeter surveillance.



Amanda Prorok is currently a Postdoctoral Researcher in the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory at the University of Pennsylvania, where she works with Prof. Vijay Kumar on heterogeneous networked robotic systems. She completed her PhD at EPFL, Switzerland, where she addressed the topic of localization with ultra-wideband sensing for robotic networks. Her dissertation was awarded the Asea Brown Boveri (ABB) award for the best thesis at EPFL in the fields of Computer Sciences, Automatics and Telecommunications.  She was selected as an MIT Rising Star in 2015, and won a Best Paper Award at BICT 2015.