Safe and Secure Networked Control Systems under Denial-of-Service Attacks

We consider the problem of security constrained optimal control for discrete-time, linear dynamical systems in which control and measurement packets are transmitted over a communication network. The packets may be jammed or compromised by a malicious adversary. For a class of denial-of-service (DoS) attack models, the goal is to find an (optimal) causal feedback controller that minimizes a given objective function subject to safety and power constraints. We present a semi-definite programming based solution for solving this problem. Our analysis also presents insights on the effect of attack models on solution of the optimal control problem.

[1]  Alexandre M. Bayen,et al.  Robust feasibility for control of water flow in a reservoir-canal system , 2007, 2007 46th IEEE Conference on Decision and Control.

[2]  James A. Primbs,et al.  Stochastic Receding Horizon Control of Constrained Linear Systems With State and Control Multiplicative Noise , 2007, IEEE Transactions on Automatic Control.

[3]  Juan C. Meza,et al.  Optimization Strategies for the Vulnerability Analysis of the Electric Power Grid , 2010, SIAM J. Optim..

[4]  Tansu Alpcan,et al.  A Decentralized Bayesian Attack Detection Algorithm for Network Security , 2008, SEC.

[5]  Eric C. Kerrigan,et al.  Optimization over state feedback policies for robust control with constraints , 2006, Autom..

[6]  J. Salmeron,et al.  Analysis of electric grid security under terrorist threat , 2004, IEEE Transactions on Power Systems.

[7]  Arkadi Nemirovski,et al.  Control of Uncertainty-Affected Discrete Time Linear Systems via Convex Programming , 2006 .

[8]  John Lygeros,et al.  Reachability Analysis for Controlled Discrete Time Stochastic Hybrid Systems , 2006, HSCC.

[9]  S. Shankar Sastry,et al.  Research Challenges for the Security of Control Systems , 2008, HotSec.

[10]  Stephen P. Boyd,et al.  Fast Model Predictive Control Using Online Optimization , 2010, IEEE Transactions on Control Systems Technology.

[11]  Robert J. Turk Cyber Incidents Involving Control Systems , 2005 .

[12]  Krishnendu Chatterjee,et al.  Termination criteria for solving concurrent safety and reachability games , 2009, SODA.

[13]  E. F. Vogel,et al.  A plant-wide industrial process control problem , 1993 .

[14]  Giuseppe Carlo Calafiore,et al.  Linear Programming with Probability Constraints - Part 2 , 2007, 2007 American Control Conference.

[15]  Thomas A. Henzinger,et al.  Hybrid Systems: Computation and Control , 1998, Lecture Notes in Computer Science.

[16]  Stephen P. Boyd,et al.  Design of Affine Controllers via Convex Optimization , 2010, IEEE Transactions on Automatic Control.

[17]  Bruno Sinopoli,et al.  Foundations of Control and Estimation Over Lossy Networks , 2007, Proceedings of the IEEE.

[18]  E. Byres,et al.  The Myths and Facts behind Cyber Security Risks for Industrial Control Systems , 2004 .

[19]  Jay H. Lee,et al.  State estimation based model predictive control applied to shell control problem: a case study , 1994 .

[20]  A. Gattami,et al.  Optimal Decisions with Limited Information , 2007 .

[21]  David Q. Mayne,et al.  Constrained model predictive control: Stability and optimality , 2000, Autom..

[22]  O. Bosgra,et al.  A full solution to the constrained stochastic closed-loop MPC problem via state and innovations feedback and its receding horizon implementation , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).