This project proposes a novel cyber-physical paradigm for enhancing the security in networks of advanced robots from external malicious cyber attacks (and internal non-malicious malfunctions as well). Such systems have tremendous potential for improved productivity, but also carry new risks: malicious actors could exploit the connectivity of the devices to carry out attacks with consequences in the physical world.<\/p>\n
The core idea of this project is to provide a novel layer of security against such threats by designing distributed security specifications based on introspection: agents use physical-sensing capabilities to surveil the behaviors of other agents in the team in addition to the task-specific mission objective. Such specifications will offer an additional layer of protection in emerging applications with networked robots.<\/span><\/p>\n Our proposed research revolves around three main thrusts: A) systematically identify attack models specific to the scenarios considered, together with countermeasures based on measurements in the physical world, B) develop abstraction-based high-level planning algorithms that generate flexible plans that satisfy both the task specifications and the additional security requirements, and C) new low-level controllers that can negotiate the high-level plans with real-time objectives (such as obstacle avoidance) while allowing for collaboration between the agents. The proposed research includes an evaluation plan on a robotic testbed which includes camera-equipped ground and aerial vehicles, as well as short-throw projectors for creating augmented reality environments emulating our motivating applications.<\/span><\/p>\n This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.<\/span><\/p>\n