Transmission scheduling for remote state estimation with quantized communication against tampering attacks

This paper studies transmission scheduling in energy-constrained multi-sensor networks under tampering attacks. From the attacker’s perspective, a stochastic tampering strategy with selective channel targeting is devised to maximize estimation degradation at a remote estimator with limited reception capacity. Concurrently, the defender employs an identification algorithm to infer the attack strategy and uses the inferred result to drive a state-compensated estimator, mitigating the attack’s impact. To reconcile the conflicting demands of accurately identifying the attack and estimating the system state under communication constraints, we derive an optimal transmission scheduling policy that balances these goals. Theoretical results are verified through simulation studies.