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Journal of Electrical and Computer Engineering
Volume 2018 (2018), Article ID 7204939, 14 pages
Research Article

A Novel Covert Agent for Stealthy Attacks on Industrial Control Systems Using Least Squares Support Vector Regression

School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China

Correspondence should be addressed to Lun Xie

Received 12 July 2017; Accepted 24 December 2017; Published 1 February 2018

Academic Editor: Vinod Sharma

Copyright © 2018 Weize Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Research on stealthiness has become an important topic in the field of data integrity (DI) attacks. To construct stealthy DI attacks, a common assumption in most related studies is that attackers have prior model knowledge of physical systems. In this paper, such assumption is relaxed and a covert agent is proposed based on the least squares support vector regression (LSSVR). By estimating a plant model from control and sensory data, the LSSVR-based covert agent can closely imitate the behavior of the physical plant. Then, the covert agent is used to construct a covert loop, which can keep the controller’s input and output both stealthy over a finite time window. Experiments have been carried out to show the effectiveness of the proposed method.