Name
Title | ||
|---|---|---|
A Novel Covert Agent for Stealthy Attacks on Industrial Control Systems Using Least Squares Support Vector Regression. |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1155/2018/7204939 | JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING |
Field | DocType | Volume |
Least squares,Data mining,Control theory,Computer science,Physical system,Support vector machine,Computer network,Covert,Input/output,Industrial control system,Data integrity | Journal | 2018 |
ISSN | Citations | PageRank |
2090-0147 | 1 | 0.35 |
References | Authors | |
13 | 3 | |