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

Handle URI:
http://hdl.handle.net/10754/564677
Title:
Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming
Authors:
Canepa, Edward S. ( 0000-0002-5779-2059 ) ; 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, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for some 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. © 2013 IEEE.
KAUST Department:
Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Distributed Sensing Systems Laboratory (DSS)
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2013 International Conference on Computing, Networking and Communications (ICNC)
Conference/Event name:
2013 International Conference on Computing, Networking and Communications, ICNC 2013
Issue Date:
Jan-2013
DOI:
10.1109/ICCNC.2013.6504104
Type:
Conference Paper
ISBN:
9781467352888
Appears in Collections:
Conference Papers; 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.authorClaudel, Christian G.en
dc.date.accessioned2015-08-04T07:11:59Zen
dc.date.available2015-08-04T07:11:59Zen
dc.date.issued2013-01en
dc.identifier.isbn9781467352888en
dc.identifier.doi10.1109/ICCNC.2013.6504104en
dc.identifier.urihttp://hdl.handle.net/10754/564677en
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, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for some 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. © 2013 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.titleSpoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programmingen
dc.typeConference Paperen
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.journal2013 International Conference on Computing, Networking and Communications (ICNC)en
dc.conference.date28 January 2013 through 31 January 2013en
dc.conference.name2013 International Conference on Computing, Networking and Communications, ICNC 2013en
dc.conference.locationSan Diego, CAen
kaust.authorClaudel, Christian G.en
kaust.authorCanepa, Edward S.en
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