Visible to the public Biblio

Filters: Author is Li, Shaoyuan  [Clear All Filters]
2023-05-12
Yao, Jingshi, Yin, Xiang, Li, Shaoyuan.  2022.  Sensor Deception Attacks Against Initial-State Privacy in Supervisory Control Systems. 2022 IEEE 61st Conference on Decision and Control (CDC). :4839–4845.
This paper investigates the problem of synthesizing sensor deception attackers against privacy in the context of supervisory control of discrete-event systems (DES). We consider a plant controlled by a supervisor, which is subject to sensor deception attacks. Specifically, we consider an active attacker that can tamper with the observations received by the supervisor. The privacy requirement of the supervisory control system is to maintain initial-state opacity, i.e., it does not want to reveal the fact that it was initiated from a secret state during its operation. On the other hand, the attacker aims to deceive the supervisor, by tampering with its observations, such that initial-state opacity is violated due to incorrect control actions. We investigate from the attacker’s point of view by presenting an effective approach for synthesizing sensor attack strategies threatening the privacy of the system. To this end, we propose the All Attack Structure (AAS) that records state estimates for both the supervisor and the attacker. This structure serves as a basis for synthesizing a sensor attack strategy. We also discuss how to simplify the synthesis complexity by leveraging the structural properties. A running academic example is provided to illustrate the synthesis procedure.
ISSN: 2576-2370
2020-05-08
Su, Yu, Wu, Jing, Long, Chengnian, Li, Shaoyuan.  2018.  Event-triggered Control for Networked Control Systems Under Replay Attacks. 2018 Chinese Automation Congress (CAC). :2636—2641.
With wide application of networked control systems(N CSs), NCSs security have encountered severe challenges. In this paper, we propose a robust event-triggered controller design method under replay attacks, and the control signal on the plant is updated only when the event-triggering condition is satisfied. We develop a general random replay attack model rather than predetermined specific patterns for the occurrences of replay attacks, which allows to obtain random states to replay. We show that the proposed event-triggered control (ETC) scheme, if well designed, can tolerate some consecutive replay attacks, without affecting the corresponding closed-loop system stability and performance. A numerical examples is finally given to illustrate the effectiveness of our method.