Distributed Attack Detection and Secure Estimation of Networked Cyber-Physical Systems Against False Data Injection Attacks and Jamming Attacks

This paper is concerned with the problem of joint distributed attack detection and distributed secure estimation for a networked cyber-physical system under physical and cyber attacks. The system is monitored by a wireless sensor network, in which a group of sensors is spatially distributed and the sensors’ measurements are broadcast to remote estimators via a wireless network medium. A malicious adversary simultaneously launches a false data injection attack at the physical system layer to intentionally modify the system's state and jamming attacks at the cyber layer to block the wireless transmission channels between sensors and remote estimators. The sensors’ measurements can be randomly dropped with mathematical probability if the corresponding transmission channels are deliberately jammed by the adversary. Resilient attack detection estimators are delicately constructed to provide locally reliable state estimations and detect the false data injection attack. Then, criteria for analyzing the estimation performance and designing the desired estimators are derived to guarantee the solvability of the problem. Finally, the effectiveness of the proposed approach is shown through an illustrative example.

[1]  Paulo Tabuada,et al.  Secure Estimation and Control for Cyber-Physical Systems Under Adversarial Attacks , 2012, IEEE Transactions on Automatic Control.

[2]  Emanuele Garone,et al.  False data injection attacks against state estimation in wireless sensor networks , 2010, 49th IEEE Conference on Decision and Control (CDC).

[3]  Richard A. Poisel,et al.  Modern Communications Jamming Principles and Techniques , 2003 .

[4]  Florian Dörfler,et al.  Attack Detection and Identification in Cyber-Physical Systems -- Part II: Centralized and Distributed Monitor Design , 2012, ArXiv.

[5]  Ruggero Carli,et al.  A distributed method for state estimation and false data detection in power networks , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[6]  Sonia Martínez,et al.  On the Performance Analysis of Resilient Networked Control Systems Under Replay Attacks , 2013, IEEE Transactions on Automatic Control.

[7]  Sebastian Engell,et al.  Gain-scheduling trajectory control of a continuous stirred tank reactor , 1998 .

[8]  Ling Shi,et al.  Optimal Denial-of-Service Attack Scheduling With Energy Constraint , 2015, IEEE Transactions on Automatic Control.

[9]  Michel Kinnaert,et al.  Diagnosis and Fault-Tolerant Control , 2006 .

[10]  Ling Shi,et al.  A Game-Theoretic Approach to Fake-Acknowledgment Attack on Cyber-Physical Systems , 2017, IEEE Transactions on Signal and Information Processing over Networks.

[11]  Qing-Long Han,et al.  Distributed event-triggered H1 filtering over sensor networks with communication delays , 2014 .

[12]  Paulo Tabuada,et al.  Event-Triggered State Observers for Sparse Sensor Noise/Attacks , 2013, IEEE Transactions on Automatic Control.

[13]  Daniel W. C. Ho,et al.  Partial-Information-Based Distributed Filtering in Two-Targets Tracking Sensor Networks , 2012, IEEE Transactions on Circuits and Systems I: Regular Papers.

[14]  Anna Scaglione,et al.  Data Injection Attacks in Randomized Gossiping , 2016, IEEE Transactions on Signal and Information Processing over Networks.

[15]  Pramod K. Varshney,et al.  Data Falsification Attacks on Consensus-Based Detection Systems , 2017, IEEE Transactions on Signal and Information Processing over Networks.

[16]  Matti Valovirta,et al.  Experimental Security Analysis of a Modern Automobile , 2011 .

[17]  Qing-Long Han,et al.  Distributed H ∞ filtering over sensor networks with heterogeneous Markovian coupling intercommunication delays , 2015 .

[18]  Peng Ning,et al.  False data injection attacks against state estimation in electric power grids , 2011, TSEC.

[19]  Qing-Long Han,et al.  Distributed networked control systems: A brief overview , 2017, Inf. Sci..

[20]  Yeung Sam Hung,et al.  Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case , 2010, Autom..

[21]  Huijun Gao,et al.  Network-Induced Constraints in Networked Control Systems—A Survey , 2013, IEEE Transactions on Industrial Informatics.

[22]  Zikuan Liu,et al.  Robust H∞ control of discrete-time Markovian jump linear systems with mode-dependent time-delays , 2001, IEEE Trans. Autom. Control..

[23]  Ling Shi,et al.  Jamming Attacks on Remote State Estimation in Cyber-Physical Systems: A Game-Theoretic Approach , 2015, IEEE Transactions on Automatic Control.

[24]  Ling Shi,et al.  Optimal DoS Attack Scheduling in Wireless Networked Control System , 2016, IEEE Transactions on Control Systems Technology.

[25]  Bruno Sinopoli,et al.  Secure Estimation in the Presence of Integrity Attacks , 2013, IEEE Transactions on Automatic Control.

[26]  Radha Poovendran,et al.  Node capture attacks in wireless sensor networks: A system theoretic approach , 2010, 49th IEEE Conference on Decision and Control (CDC).

[27]  Xin-Ping Guan,et al.  Distributed optimal consensus filter for target tracking in heterogeneous sensor networks , 2011, 2011 8th Asian Control Conference (ASCC).

[28]  Long Wang,et al.  Robust fault detection with missing measurements , 2008, Int. J. Control.

[29]  Sonia Martínez,et al.  On distributed constrained formation control in operator-vehicle adversarial networks , 2013, Autom..

[30]  C. I. Chihaia,et al.  Active fault-tolerance in wireless networked control systems , 2010 .

[31]  Bruno Sinopoli,et al.  Detecting Integrity Attacks on SCADA Systems , 2011 .

[32]  Qing-Long Han,et al.  Absolute stability of time-delay systems with sector-bounded nonlinearity , 2005, Autom..

[33]  Qing-Long Han,et al.  Distributed fault detection over sensor networks with Markovian switching topologies , 2014, Int. J. Gen. Syst..