Likelihood Ratio Based Scheduler for Secure Detection in Cyber Physical Systems
For designers of secure cyber-physical systems, this work provides a scheduler that maintains detection functionality under attacks with graceful degradation, addressing a practical bottleneck in secure networked detection.
This paper proposes a likelihood ratio based scheduler for secure binary detection in cyber-physical systems under communication rate constraints and cyber attacks. The scheduler achieves asymptotic detection performance comparable to the Neyman-Pearson test with full measurements under moderate rate constraints, and outperforms random scheduling.
This paper is concerned with a binary detection problem over a non-secure network. To satisfy the communication rate constraint and against possible cyber attacks, which are modeled as deceptive signals injected to the network, a likelihood ratio based (LRB) scheduler is designed in the sensor side to smartly select sensor measurements for transmission. By exploring the scheduler, some sensor measurements are successfully retrieved from the attacked data at the decision center. We show that even under a moderate communication rate constraint of secure networks, an optimal LRB scheduler can achieve a comparable asymptotic detection performance to the standard N-P test using the full set of measurements, and is strictly better than the random scheduler. For non-secure 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.