Robust detection of biasing attacks on misappropriated distributed observers via decentralized H∞ synthesis

We develop a decentralized H∞ synthesis approach to detection of biasing misappropriation attacks on distributed observers. Its starting point is to equip the observer with an attack model which is then used in the design of attack detectors. A two-step design procedure is proposed. First, an initial centralized setup is carried out which enables each node to compute the parameters of its attack detector online in a decentralized manner, without interacting with other nodes. Each such detector is designed using the H∞ approach. Next, the attack detectors are embedded into the network, which allows them to detect misappropriated nodes from innovation in the network interconnections.

[1]  Valery A. Ugrinovskii,et al.  Detection of biasing attacks on distributed estimation networks , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

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

[3]  Valery A. Ugrinovskii,et al.  Minimum-energy distributed filtering , 2014, 53rd IEEE Conference on Decision and Control.

[4]  Roy S. Smith,et al.  Covert Misappropriation of Networked Control Systems: Presenting a Feedback Structure , 2015, IEEE Control Systems.

[5]  Henrik Sandberg,et al.  Stealth Attacks and Protection Schemes for State Estimators in Power Systems , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[6]  V A Ugrinovskii,et al.  Distributed robust filtering with H∞ consensus of estimates , 2010, Proceedings of the 2010 American Control Conference.

[7]  T. Basar,et al.  H∞-0ptimal Control and Related Minimax Design Problems: A Dynamic Game Approach , 1996, IEEE Trans. Autom. Control..

[8]  Valery Ugrinovskii,et al.  Distributed H ∞ consensus-based estimation of uncertain systems via dissipativity theory , 2011 .

[9]  Valery A. Ugrinovskii,et al.  Gain-scheduled synchronization of parameter varying systems via relative H∞ consensus with application to synchronization of uncertain bilinear systems , 2014, Autom..

[10]  Reza Olfati-Saber,et al.  Distributed Kalman filtering for sensor networks , 2007, 2007 46th IEEE Conference on Decision and Control.

[11]  Luca Schenato,et al.  A Survey on Distributed Estimation and Control Applications Using Linear Consensus Algorithms , 2010 .

[12]  Valery A. Ugrinovskii,et al.  Distributed robust estimation over randomly switching networks using H∞ consensus , 2015, Autom..

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

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

[15]  Valery A. Ugrinovskii,et al.  Distributed robust filtering with Hinfinity consensus of estimates , 2011, Autom..

[16]  Henrik Sandberg,et al.  Distributed Fault Detection and Isolation Resilient to Network Model Uncertainties , 2014, IEEE Transactions on Cybernetics.