Time Synchronization Attack and Countermeasure for Multi-System Scheduling in Remote Estimation
For CPS security researchers, this work addresses a novel attack vector on multi-sensor scheduling, but the results are incremental as they extend known attack-countermeasure frameworks to a specific scenario.
This paper investigates time synchronization attacks against multi-system scheduling in remote estimation, showing that an attacker can cause the expected estimation error covariance to diverge without system knowledge. A countermeasure using shift-invariant transmission policies is proposed, with bounds on estimation performance.
We consider time synchronization attack against multi-system scheduling in a remote state estimation scenario where a number of sensors monitor different linear dynamical processes and schedule their transmissions through a shared collision channel. We show that by randomly injecting relative time offsets on the sensors, the malicious attacker is able to make the expected estimation error covariance of the overall system diverge without any system knowledge. For the case that the attacker has full system information, we propose an efficient algorithm to calculate the optimal attack, which spoofs the least number of sensors and leads to unbounded average estimation error covariance. To mitigate the attack consequence, we further propose a countermeasure by constructing shift invariant transmission policies and characterize the lower and upper bounds for system estimation performance. Simulation examples are provided to illustrate the obtained results.