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
  • [21] Cyber Attacks in Cyber-Physical Microgrid Systems: A Comprehensive Review
    Suprabhath Koduru, Sriranga
    Machina, Venkata Siva Prasad
    Madichetty, Sreedhar
    ENERGIES, 2023, 16 (12)
  • [22] Anomaly Identification for Cyber-Physical Systems Subject to Replay Attacks and Sensor Faults
    Hu, Yuxiang
    Dai, Xuewu
    Cui, Dongliang
    Liu, Qiang
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2024, 71 (12) : 5044 - 5048
  • [23] Detection and Identification of Sparse Sensor Attacks in Cyber-Physical Systems With Side Information
    Lu, An-Yang
    Yang, Guang-Hong
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2023, 68 (09) : 5349 - 5364
  • [24] Coordinated cyber-physical attacks of cyber-physical power system
    Yang Y.
    Lan S.
    Qin Z.
    Liu H.
    Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2020, 40 (02): : 97 - 102
  • [25] Detection and Isolation of DoS and Integrity Cyber Attacks in Cyber-Physical Systems with a Neural Network-Based Architecture
    Paredes, Carlos M.
    Martinez-Castro, Diego
    Ibarra-Junquera, Vrani
    Gonzalez-Potes, Apolinar
    ELECTRONICS, 2021, 10 (18)
  • [26] Modeling Cyber-Physical Systems for Automatic Verification
    Driouich, Youssef
    Parente, Mimmo
    Tronci, Enrico
    2017 14TH INTERNATIONAL CONFERENCE ON SYNTHESIS, MODELING, ANALYSIS AND SIMULATION METHODS AND APPLICATIONS TO CIRCUIT DESIGN (SMACD), 2017,
  • [27] On Data Integrity Attacks against Route Guidance in Transportation-based Cyber-Physical Systems
    Lin, Jie
    Yu, Wei
    Zhang, Nan
    Yang, Xinyu
    Ge, Linqiang
    2017 14TH IEEE ANNUAL CONSUMER COMMUNICATIONS & NETWORKING CONFERENCE (CCNC), 2017, : 313 - 318
  • [28] Adaptive control-theoretic detection of integrity attacks against cyber-physical industrial systems
    Rubio-Hernan, Jose
    De Cicco, Luca
    Garcia-Alfaro, Joaquin
    TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2018, 29 (07):
  • [29] Defending Cyber-Physical Systems against DoS Attacks
    Nur, Abdullah Yasin
    Tozal, Mehmet Engin
    2016 IEEE INTERNATIONAL CONFERENCE ON SMART COMPUTING (SMARTCOMP), 2016, : 334 - 336
  • [30] Relational Analysis of Sensor Attacks on Cyber-Physical Systems
    Xiang, Jian
    Fulton, Nathan
    Chong, Stephen
    2021 IEEE 34TH COMPUTER SECURITY FOUNDATIONS SYMPOSIUM (CSF 2021), 2021, : 249 - 264