Publications

Cyber-Physical Systems (CPS) such as Unmanned Aerial Systems (UAS) sense and actuate their environment in pursuit of a mission. The attack surface of these remotely located, sensing and communicating devices is both large, and exposed to adversarial actors, making mission assurance a challenging problem. While best-practice security policies should be followed, they are rarely enough to guarantee mission success as not all components in the system may be trusted and the properties of the environment (e.g., the RF environment) may be under the control of the attacker. CPS must thus be built with a high degree of resilience to mitigate threats that security cannot alleviate. In this paper, we describe the Agile and Resilient Embedded Systems (ARES) methodology and metric set. The ARES methodology pursues cyber security and resilience (CSR) as high level system properties to be developed in the context of the mission. An analytic process guides system developers in defining mission objectives, examining principal issues, applying CSR technologies, and understanding their interactions.

Tactical high-energy laser (HEL) systems face a range of imaging-related challenges in wavefront sensing, acquiring and tracking targets, selecting the HEL aimpoint, and assessing lethality. Accomplishing these functions in a timely fashion may be limited by competing requirements on total field of regard, target resolution, signal to noise, and focal plane readout bandwidth. In this paper, we explore the applicability of an emerging pixel-processing imager (PPI) technology to these challenges. The on-focal-plane signal processing capabilities of the MIT Lincoln Laboratory PPI technology have recently been extended in support of directed energy applications. We describe this work as well as early results from a new PPI-based short-wave-infrared focal plane readout capable of supporting diverse applications such as low-latency Shack-Hartmann wavefront sensing, centroid computation, and Fitts correlation tracking.