Sparse attacking strategies in multi-sensor dynamic systems maximizing state estimation errors

Jingyang Lu; Ruixin Niu

ICASSP 2016accepted0 citations

Sparse attacking strategies in multi-sensor dynamic systems maximizing state estimation errors

Abstract

In this paper, from the adversary's point of view, the optimal strategy to attack a multi-sensor dynamic system is investigated. It is assumed that the system can perfectly detect and remove sensors once they are corrupted by false information injected by an adversary. The adversary is trying to maximize the covariance matrix of the system state estimate by the end of attack period under the constraint that the adversary can only attack the system a few times over time and over sensors, which leads to an integer programming problem. The exhaustive search algorithm has a prohibitive complexity and greedy algorithms are proposed to find the attack strategies. Examples and numerical results are provided in order to illustrate the effectiveness of the proposed attack strategies.

BibTeX

@inproceedings{icassp2016_sparseattackings,
  title = {Sparse attacking strategies in multi-sensor dynamic systems maximizing state estimation errors},
  author = {Jingyang Lu and Ruixin Niu},
  booktitle = {ICASSP 2016},
  year = {2016}
}