# American Institute of Mathematical Sciences

September  2013, 8(3): 783-802. doi: 10.3934/nhm.2013.8.783

## Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming

 1 King Abdullah University of Science and Technology, Electrical Engineering Department, Thuwal, Makkah 23955, KSA, Saudi Arabia, Saudi Arabia 2 University of California at Berkely, Electrical Engineering and Computer Sciences, Berkeley CA 94720-170

Received  September 2012 Revised  March 2013 Published  October 2013

Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill-Whitham-Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data generated by multiple sensors of different types, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for a specific decision variable. We use this fact to pose the problem of detecting spoofing cyber attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offline. A numerical implementation is performed on a cyber attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California.
Citation: Edward S. Canepa, Alexandre M. Bayen, Christian G. Claudel. Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming. Networks & Heterogeneous Media, 2013, 8 (3) : 783-802. doi: 10.3934/nhm.2013.8.783
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