Enhancing Cyber-Physical Systems (CPS) robustness through sensor-pair health indicator

Real-time collection of reliable sensor information for the computing elements of Autonomous Systems (ASs) is crucial for execution of tasks that protect human lives and strategic assets. Both Cyber-Physical Systems (CPS), and the Internet of Things (IoT), heavily rely on dependable sensor data to perform their functions. We propose the utilization of a sensor-based Physically Unclonable Function (PUF) to detect the health of the sensor itself; without imposing restrictions on its potential application for cryptographic authentication, identification and key generation in future endeavors. Two key considerations are emphasized: (1) in the absence of sensor malfunction, predictable responses are anticipated and (2) if the sensor is malfunctioning then there should be a noticeable shift in the responses; indicating the need for replacement or the disregard of sensor data information (which may prevent an unintended outcome that may otherwise occur). We conduct an examination of both intra and inter aspects of the accelerometer-PUF. Furthermore, a dedicated section is included to present the outcomes of health detection based on the sensor pairs' responses. Additionally, we perform temperature testing to measure the reproducibility of the PUF under varying conditions; encompassing both cold and hot temperatures over the range −20^◦C < T > 50^◦C.