Synthesizing Attack-Aware Control and Active Sensing Strategies under Reactive Sensor Attacks

TL;DR

This paper develops a probabilistic planning framework for a defender to reach goal states while actively sensing and countering sensor attacks by an adversary, using a stochastic game model with belief states.

Contribution

It introduces a novel attack-aware control and sensing synthesis method using a stochastic game with augmented states for provable security against sensor attacks.

Findings

Algorithm guarantees reachability with probability one under worst-case attacks

Constructs belief-based randomized strategies for the defender

Proves correctness of the proposed synthesis method

Abstract

We consider the probabilistic planning problem for a defender (P1) who can jointly query the sensors and take control actions to reach a set of goal states while being aware of possible sensor attacks by an adversary (P2) who has perfect observations. To synthesize a provably-correct, attack-aware joint control and active sensing strategy for P1, we construct a stochastic game on graph with augmented states that include the actual game state (known only to the attacker), the belief of the defender about the game state (constructed by the attacker based on his knowledge of defender's observations). We present an algorithm to compute a belief-based, randomized strategy for P1 to ensure satisfying the reachability objective with probability one, under the worst-case sensor attack carried out by an informed P2. We prove the correctness of the algorithm and illustrate using an example.