Optimal Denial-of-Service Attacks Against Partially-Observable Real-Time Monitoring Systems

TL;DR

This paper analyzes optimal strategies for adversaries to perform denial-of-service attacks on cyber-physical systems with multiple sensors, balancing attack effectiveness and energy use, using advanced decision models.

Contribution

It introduces a novel framework for optimal jamming policies in partially observable systems, employing threshold and Whittle's index policies for single and multiple sources.

Findings

Optimal threshold jamming policy for single-source systems.

Whittle's index-based policy for multi-source scenarios.

Numerical results show improved attack strategies over baselines.

Abstract

In this paper, we investigate the impact of denial-of-service attacks on the status updating of a cyber-physical system with one or more sensors connected to a remote monitor via unreliable channels. We approach the problem from the perspective of an adversary that can strategically jam a subset of the channels. The sources are modeled as Markov chains, and the performance of status updating is measured based on the age of incorrect information at the monitor. Our objective is to derive jamming policies that strike a balance between the degradation of the system's performance and the conservation of the adversary's energy. For a single-source scenario, we formulate the problem as a partially-observable Markov decision process, and rigorously prove that the optimal jamming policy is of a threshold form. We then extend the problem to a multi-source scenario. We formulate this problem as a restless multi-armed bandit, and provide a jamming policy based on the Whittle's index. Our numerical results highlight the performance of our policies compared to baseline policies.