Likelihood Ratio-Based Scheduler for Secure Detection in Cyber Physical Systems

This paper is concerned with a binary detection problem over a nonsecure network. To satisfy the communication constraint and against possible cyber attacks, which are modeled as jamming signals injected to the network, a likelihood ratio based (LRB) scheduler is designed in the sensor to smartly select informative sensor measurements for transmission. We show that even under a moderate transmission rate constraint of secure networks, an optimal LRB scheduler can achieve a comparable asymptotic detection performance to the standard Neyman-Pearson test using the full set of measurements, and is strictly better than the random scheduler. For nonsecure networks, the LRB scheduler can also maintain the detection functionality but suffers graceful performance degradation under different attack intensities. Finally, we perform simulations to validate our theoretical results.