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

Handle URI:
http://hdl.handle.net/10754/562948
Title:
Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming
Authors:
Canepa, Edward S. ( 0000-0002-5779-2059 ) ; Bayen, Alexandre M.; Claudel, Christian G. ( 0000-0003-0702-6548 )
Abstract:
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 offliine. 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. © American Institute of Mathematical Sciences.
KAUST Department:
Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Distributed Sensing Systems Laboratory (DSS)
Publisher:
American Institute of Mathematical Sciences (AIMS)
Journal:
Networks and Heterogeneous Media
Issue Date:
Sep-2013
DOI:
10.3934/nhm.2013.8.783
Type:
Article
ISSN:
15561801
Appears in Collections:
Articles; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorCanepa, Edward S.en
dc.contributor.authorBayen, Alexandre M.en
dc.contributor.authorClaudel, Christian G.en
dc.date.accessioned2015-08-03T11:16:40Zen
dc.date.available2015-08-03T11:16:40Zen
dc.date.issued2013-09en
dc.identifier.issn15561801en
dc.identifier.doi10.3934/nhm.2013.8.783en
dc.identifier.urihttp://hdl.handle.net/10754/562948en
dc.description.abstractTraffic 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 offliine. 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. © American Institute of Mathematical Sciences.en
dc.publisherAmerican Institute of Mathematical Sciences (AIMS)en
dc.titleSpoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programmingen
dc.typeArticleen
dc.contributor.departmentElectrical Engineering Programen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentDistributed Sensing Systems Laboratory (DSS)en
dc.identifier.journalNetworks and Heterogeneous Mediaen
dc.contributor.institutionUniversity of California at Berkely, Electrical Engineering and Computer Sciences, Berkeley CA 94720-170, United Statesen
kaust.authorClaudel, Christian G.en
kaust.authorCanepa, Edward S.en
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