A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 2 Issue 3
Jul.  2015

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 15.3, Top 1 (SCI Q1)
    CiteScore: 23.5, Top 2% (Q1)
    Google Scholar h5-index: 77, TOP 5
Turn off MathJax
Article Contents
Yumei Li, Holger Voos, Mohamed Darouach and Changchun Hua, "An Algebraic Detection Approach for Control Systems under Multiple Stochastic Cyber-attacks," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 3, pp. 258-266, 2015.
Citation: Yumei Li, Holger Voos, Mohamed Darouach and Changchun Hua, "An Algebraic Detection Approach for Control Systems under Multiple Stochastic Cyber-attacks," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 3, pp. 258-266, 2015.

An Algebraic Detection Approach for Control Systems under Multiple Stochastic Cyber-attacks

Funds:

This work was supported by the Fonds National de la Recherche, Luxembourg (CO11/IS/1206050 (SeSaNet)) and National Natural Science Foundation of China (61273222).

  • In order to compromise a target control system successfully, hackers possibly attempt to launch multiple cyberattacks aiming at multiple communication channels of the control system. However, the problem of detecting multiple cyber-attacks has been hardly investigated so far. Therefore, this paper deals with the detection of multiple stochastic cyber-attacks aiming at multiple communication channels of a control system. Our goal is to design a detector for the control system under multiple cyberattacks. Based on frequency-domain transformation technique and auxiliary detection tools, an algebraic detection approach is proposed. By applying the presented approach, residual information caused by different attacks is obtained respectively and anomalies in the control system are detected. Sufficient and necessary conditions guaranteeing the detectability of the multiple stochastic cyber-attacks are obtained. The presented detection approach is simple and straightforward. Finally, two simulation examples are provided, and the simulation results show that the detection approach is effective and feasible.

     

  • loading
  • [1]
    Bier V, Oliveros S, Samuelson L. Choosing what to protect:strategic defensive allocation against an unknown attacker. Journal of Public Economic Theory, 2007, 9(4):563-587
    [2]
    Amin S, Schwartz G A, Sastry S S. Security of interdependent and identical networked control systems. Automatica, 2013, 49(1):186-192
    [3]
    Slay J, Miller M. Lessons learned from the Maroochy water breach. Critical Infrastructure Protection, 2007, 253:73-82
    [4]
    Andersson G, Esfahani P M, Vrakopoulou M, Margellos K, Lygeros J, Teixeira A, Dan G, Sanderg H, Johansson K H. Cyber-security of SCADA systems. Session:Cyber-Physical System Security in a Smart Grid Environment, 2011.
    [5]
    Mo Y L, Sinopoli B. False data injection attacks in control systems. In:Proceedings of the 1st Workshop on Secure Control Systems. Stockholm, Sweden, 2010.
    [6]
    Amin S, Litrico X, Sastry S, Bayen A M. Cyber security of water SCADA systems:(I) analysis and experimentation of stealthy deception attacks. IEEE Transactions on Control Systems Technology, 2013, 21(5):1963-1970
    [7]
    Eliades D G, Polycarpou M M. A fault diagnosis and security framework for water systems. IEEE Transactions on Control Systems Technology, 2010, 18(6):1254-1265
    [8]
    Metke A R, Ekl R L. Security technology for smart grid networks. IEEE Transactions on Smart Grid, 2010, 1(1):99-107
    [9]
    Sridhar S, Hahn A, Govindarasu M. Cyber-physical system security for the electric power grid. Proceedings of the IEEE, 2012, 100(1):210-224
    [10]
    Mohsenian-Rad A H, Leon-Garcia A. Distributed internet-based load altering attacks against smart power grids. IEEE Transactions on Smart Grid, 2011, 2(4):667-674
    [11]
    Sardana A, Joshi R C. Dual-level attack detection and characterization for networks under DDoS. In:Proceedings of the 2010 International Conference on Availability, Reliability and Security. Krakow:IEEE, 2010. 9-16
    [12]
    Weimer J, Kar S, Johansson K H. Distributed detection and isolation of topology attacks in power networks. In:Proceedings of the 2012 HiCoNS012. Beijing, China, 2012. 17-18
    [13]
    Liu Y, Reiter M K, Ning P. False data injection attacks against state estimation in electric power grids. In:Proceedings of the 2009 ACM Conference on Computer and Communications Security. Chicago, IL, USA:ACM, 2009. 21-32
    [14]
    Rosich A, Voos H, Li Y M, Darouach M. A model predictive approach for cyber-attack detection and mitigation in control systems. In:Proceedings of the 52nd Annual Conference on Decision and Control. Firenze:IEEE, 2013. 6621-6626
    [15]
    Li Y M, Voos H, Rosich A, Darouach M. A stochastic cyber-attack detection scheme for stochastic control systems based on frequencydomain transformation technique. In:Proceedings of the 8th International Conference on Network and System Security. Xi'an, China:Springer, 2014. 209-222
    [16]
    Li Y M, Voos H, Darouach M. Robust H fault estimation for control systems under stochastic cyber-attacks. In:Proceedings of the 33rd Chinese Control Conference. Nanjing, China:ORBilu, 2014. 3124-3129
    [17]
    Hashim F, Kibria M R, Jamalipour A. Detection of DoS and DDoS attacks in NGMN using frequency domain analysis. In:Proceedings of the 14th Asia-Pacific Conference on Communications. Tokyo:IEEE, 2008. 1-5
    [18]
    Sundaram S, Hadjicostis C N. Distributed function calculation via linear iterative strategies in the presence of malicious agents. IEEE Transactions on Automatic Control, 2011, 56(7):1495-1508
    [19]
    Teixeira A, Sandberg H, Johansson K H. Networked control systems under cyber attacks with applications to power networks. In:Proceedings of the 2010 American Control Conference. Baltimore, MD:IEEE, 2010. 3690-3696
    [20]
    Pasqualetti F, Bichi A, Bullo F. Consensus computation in unreliable networks:a system theoretic approach. IEEE Transactions on Automatic Control, 2012, 57(1):90-104
    [21]
    Johansson K H. The quadruple-tank process:a multivariable laboratory process with an adjustable zero. IEEE Transactions on Control Systems Technology, 2000, 8(3):456-465
    [22]
    Zhou K M, Doyle J C, Glover K. Robust and Optimal Control. Upper Saddle River, NJ, USA:Prentice-Hall, Inc., 1996.

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (1307) PDF downloads(13) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return