Automatic identification of integrity attacks in cyber-physical systems

被引:37
|
作者
Ntalampiras, Stavros [1 ]
机构
[1] Politecn Milan, Dept Elect Informat & Bioengn, I-20133 Milan, Italy
关键词
Critical infrastructure protection; Fault diagnosis; Cyber security; Cyber-physical systems; Probabilistic modelling; Deep learning; BAD DATA; SMART; SECURITY;
D O I
10.1016/j.eswa.2016.04.006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Modern society relies on the availability and smooth operation of complex engineering systems, such as electric power systems, water distributions networks, etc. which due to the recent advancements in information and communication technologies (ICT) are usually controlled by means of a cyber-layer. This design may potentially improve the usage of the components of the cyber-physical system (CPS), however further protection is needed due to the emerging threat of cyber-attacks. These may degrade the quality of the communicated information which is of fundamental importance in the decision making process. This paper proposes a novel methodology for automatic identification of the type of the integrity attack affecting a CPS. We designed a feature set for capturing the characteristics of each attack in the spectral and wavelet domains while its distribution is learned by pattern recognition algorithms of different modelling properties customized for the specific application scenario. In addition a novelty detection component is incorporated for dealing with previously unseen types of attacks. The proposed approach is applied onto data coming from the IEEE-9 bus model achieving promising identification performance. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:164 / 173
页数:10
相关论文
共 50 条
  • [41] Learning-Based Attacks in Cyber-Physical Systems
    Khojasteh, Mohammad Javad
    Khina, Anatoly
    Franceschetti, Massimo
    Javidi, Tara
    IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2021, 8 (01): : 437 - 449
  • [42] Robustness of Asymmetric Cyber-Physical Power Systems Against Cyber Attacks
    Lai, Rong
    Qiu, Xiaoyu
    Wu, Jiajing
    IEEE ACCESS, 2019, 7 : 61342 - 61352
  • [43] Security Control of Cyber-Physical Systems under Cyber Attacks: A Survey
    Xing, Wei
    Shen, Jun
    SENSORS, 2024, 24 (12)
  • [44] Detecting covert channel attacks on cyber-physical systems
    Li, Hongwei
    Chasaki, Danai
    IET CYBER-PHYSICAL SYSTEMS: THEORY & APPLICATIONS, 2024, 9 (03) : 228 - 237
  • [45] Security of SCADA Systems Against Cyber-Physical Attacks
    Do, Van Long
    Fillatre, Lionel
    Nikiforov, Igor
    Willett, Peter
    IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE, 2017, 32 (05) : 28 - 45
  • [46] Adversarial Attacks and Defenses on Cyber-Physical Systems: A Survey
    Li, Jiao
    Liu, Yang
    Chen, Tao
    Xiao, Zhen
    Li, Zhenjiang
    Wang, Jianping
    IEEE INTERNET OF THINGS JOURNAL, 2020, 7 (06) : 5103 - 5115
  • [47] Optimal Data Injection Attacks in Cyber-Physical Systems
    Wu, Guangyu
    Sun, Jian
    Chen, Jie
    IEEE TRANSACTIONS ON CYBERNETICS, 2018, 48 (12) : 3302 - 3312
  • [48] A Tutorial on Detecting Security Attacks on Cyber-Physical Systems
    Griffioen, Paul
    Weerakkody, Sean
    Ozel, Omur
    Mo, Yilin
    Sinopoli, Bruno
    2019 18TH EUROPEAN CONTROL CONFERENCE (ECC), 2019, : 979 - 984
  • [49] Adversarial Regression for Detecting Attacks in Cyber-Physical Systems
    Ghafouri, Amin
    Vorobeychik, Yevgeniy
    Koutsoukos, Xenofon
    PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2018, : 3769 - 3775
  • [50] Reliability Analysis of Cyber-Physical Systems Considering Cyber-Attacks
    Fang, Z. H.
    Mo, H. D.
    Wang, Y.
    2017 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEM), 2017, : 364 - 368