Network steganography based security framework for cyber-physical systems

被引:7
|
作者
Zhang, Xiao-Guang [1 ,3 ]
Yang, Guang-Hong [1 ,2 ]
Ren, Xiu-Xiu [1 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Liaoning, Peoples R China
[3] Shanghai Intelligent Qual Technol Co Ltd, Shanghai 201801, Peoples R China
基金
中国国家自然科学基金;
关键词
Cyber-physical systems; Network steganography; Covert channel; Attack detection; Eavesdropping attack defense; REMOTE STATE ESTIMATION; ATTACKS;
D O I
10.1016/j.ins.2022.07.081
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a novel network steganography (NS) based security framework to ensure the security operation of the cyber-physical systems (CPSs). Firstly, a new covert channel is established to conceal the existence of the secret data exchange by exploiting the dynamical system's measurements with no extra communication overhead. The covert channel evades the imperceptible and statistical detections in an effective manner. Next, combining covert transmission with data consistency, a data-based attack detection methodology is explored, which is capable of detecting a broad class of cyber-attacks and differs from the existing detection methods that enhance detection performance by degrading system performance or adding redundant systems. Then, combining covert transmission with simple linear encryption, an eavesdropping defense methodology is pro-posed, which guarantees that the authorized user's estimation performance is optimal and renders the eavesdropper's error covariance unbounded. Moreover, the detection and defense methods take small memory and computational overhead of the embedded sys-tem, which ensures the ease of implementation in real-world systems. Finally, the effec-tiveness of the proposed security framework is demonstrated by a proof-of-concept implementation on a CPS prototype called permanent magnet synchronous machine (PMSM) monitoring system.(c) 2022 Elsevier Inc. All rights reserved.
引用
收藏
页码:963 / 983
页数:21
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