Testing and Defending Methods Against DOS Attack in State Estimation

In this paper, we consider a state estimation problem. In this problem, a sensor measures the state of a linear discrete-time system and sends measurements to an estimator via a packet-dropping communication link. We are concerned with the effect of Denial-of-Service (DoS) attacks on stability of the estimation system, and particularly focus on how to examine whether the communication channel is under DoS attack or not as well as how to defend accordingly, if defense is possible. We formulate the detection problem as a hypothesis testing problem provided that the statistics of the communication channel is known a priori. Two defense countermeasures are proposed: one of which uses a secured packet coding approach to partly compensate the previous packet loss; and in the other the sensor's transmission power is raised to resist the jamming effect brought by the DoS attack. Simulations are provided to demonstrate the main results.

[1]  S. Shankar Sastry,et al.  Safe and Secure Networked Control Systems under Denial-of-Service Attacks , 2009, HSCC.

[2]  Jiming Chen,et al.  Mobility and Intruder Prior Information Improving the Barrier Coverage of Sparse Sensor Networks , 2014, IEEE Transactions on Mobile Computing.

[3]  Robert J. Elliott,et al.  On Finite-State Stochastic Modeling and Secure Estimation of Cyber-Physical Systems , 2017, IEEE Transactions on Automatic Control.

[4]  Jiming Chen,et al.  Collaborative Estimation and Actuation for Wireless Sensor and Actuator Networks , 2014 .

[5]  Panganamala Ramana Kumar,et al.  The transport capacity of wireless networks over fading channels , 2004, IEEE Transactions on Information Theory.

[6]  Jiming Chen,et al.  Dynamic sensor data scheduling for remote estimation over Gilbert-Elliot channel , 2014, 2014 IEEE/CIC International Conference on Communications in China (ICCC).

[7]  Bruno Sinopoli,et al.  Kalman filtering with intermittent observations , 2004, IEEE Transactions on Automatic Control.

[8]  Chen Junyong,et al.  Intermittent quantized Kalman filtering and LQG control based on Lloyd-Max quantizer , 2012, Proceedings of the 31st Chinese Control Conference.

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

[10]  Mohsen Guizani,et al.  Securing Cognitive Radio Networks against Primary User Emulation Attacks , 2016, IEEE Network.

[11]  Youxian Sun,et al.  Guaranteed Performance Control of DFIG Variable-Speed Wind Turbines , 2016, IEEE Transactions on Control Systems Technology.

[12]  Bruno Sinopoli,et al.  Optimal linear LQG control over lossy networks without packet acknowledgment , 2008 .

[13]  Karl Henrik Johansson,et al.  A secure control framework for resource-limited adversaries , 2012, Autom..

[14]  Fengzhong Qu,et al.  Performance of Target Tracking in Radar Network System Under Deception Attack , 2015, WASA.

[15]  Dae-Wha Seo,et al.  Intrusion detection based on traffic analysis in wireless sensor networks , 2010, The 19th Annual Wireless and Optical Communications Conference (WOCC 2010).

[16]  Jiming Chen,et al.  Building-Environment Control With Wireless Sensor and Actuator Networks: Centralized Versus Distributed , 2010, IEEE Transactions on Industrial Electronics.

[17]  Dan Rubenstein,et al.  Using Channel Hopping to Increase 802.11 Resilience to Jamming Attacks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

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

[19]  Joel Max,et al.  Quantizing for minimum distortion , 1960, IRE Trans. Inf. Theory.

[20]  Ling Shi,et al.  Event-Based Sensor Data Scheduling: Trade-Off Between Communication Rate and Estimation Quality , 2013, IEEE Transactions on Automatic Control.

[21]  Jiming Chen,et al.  Privacy and performance trade-off in cyber-physical systems , 2016, IEEE Network.

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

[23]  Wenyuan Xu,et al.  The feasibility of launching and detecting jamming attacks in wireless networks , 2005, MobiHoc '05.

[24]  Xiaoyu Wang,et al.  Distributed Load Sharing of an Inverter-Based Microgrid With Reduced Communication , 2018, IEEE Transactions on Smart Grid.

[25]  Ling Shi,et al.  How Can Online Schedules Improve Communication and Estimation Tradeoff? , 2013, IEEE Transactions on Signal Processing.

[26]  Yu Cheng,et al.  Real-Time Misbehavior Detection and Mitigation in Cyber-Physical Systems Over WLANs , 2017, IEEE Transactions on Industrial Informatics.

[27]  Lingkun Fu,et al.  DoS Attack Energy Management Against Remote State Estimation , 2018, IEEE Transactions on Control of Network Systems.

[28]  Ling Shi,et al.  Optimal Denial-of-Service attack scheduling against linear quadratic Gaussian control , 2014, 2014 American Control Conference.

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

[30]  Yu Cheng,et al.  Ghost-in-ZigBee: Energy Depletion Attack on ZigBee-Based Wireless Networks , 2016, IEEE Internet of Things Journal.

[31]  Qian Zhang,et al.  hJam: Attachment Transmission in WLANs , 2013, IEEE Trans. Mob. Comput..

[32]  Minyue Fu,et al.  Kalman Filtering Over Lossy Networks Under Switching Sensors , 2015 .

[33]  Pietro Tesi,et al.  Resilient Control under Denial-of-Service , 2013, ArXiv.

[34]  Ling Shi,et al.  An innovative packet-splitting approach for kalman filtering over lossy networks , 2011, Proceedings of the 2011 American Control Conference.

[35]  Ling Shi,et al.  Event-triggered maximum likelihood state estimation , 2014, Autom..

[36]  Wei Xing Zheng,et al.  Distributed ℋ∞ Filtering for a Class of Discrete-Time Markov Jump Lur'e Systems With Redundant Channels , 2016, IEEE Trans. Ind. Electron..

[37]  Ling Shi,et al.  On Set-Valued Kalman Filtering and Its Application to Event-Based State Estimation , 2015, IEEE Transactions on Automatic Control.