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dc.contributor.authorLaszka, Aron
dc.contributor.authorPotteiger, Bradley
dc.contributor.authorVorobeychik, Yevgeniy
dc.contributor.authorAmin, Saurabh
dc.contributor.authorKoutsoukos, Xenofon
dc.date.accessioned2017-06-23T13:54:21Z
dc.date.available2017-06-23T13:54:21Z
dc.date.issued2016-05
dc.date.submitted2016-04
dc.identifier.isbn978-1-5090-1772-0
dc.identifier.urihttp://hdl.handle.net/1721.1/110202
dc.description.abstractTraffic signals were originally standalone hardware devices running on fixed schedules, but by now, they have evolved into complex networked systems. As a consequence, traffic signals have become susceptible to attacks through wireless interfaces or even remote attacks through the Internet. Indeed, recent studies have shown that many traffic lights deployed in practice have easily exploitable vulnerabilities, which allow an attacker to tamper with the configuration of the signal. Due to hardware-based failsafes, these vulnerabilities cannot be used to cause accidents. However, they may be used to cause disastrous traffic congestions. Building on Daganzo's well- known traffic model, we introduce an approach for evaluating vulnerabilities of transportation networks, identifying traffic signals that have the greatest impact on congestion and which, therefore, make natural targets for attacks. While we prove that finding an attack that maximally impacts congestion is NP-hard, we also exhibit a polynomial-time heuristic algorithm for computing approximately optimal attacks. We then use numerical experiments to show that our algorithm is extremely efficient in practice. Finally, we also evaluate our approach using the SUMO traffic simulator with a real-world transportation network, demonstrating vulnerabilities of this network. These simulation results extend the numerical experiments by showing that our algorithm is extremely efficient in a microsimulation model as well.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Award CNS-1238959)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Award CNS-1238962)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Award CNS- 1239054)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Award CNS-1239166)en_US
dc.description.sponsorshipUnited States. Air Force. Research Laboratory (Award FA8750-14-2-0180)en_US
dc.description.sponsorshipSandia National Laboratoriesen_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICCPS.2016.7479122en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceOther repositoryen_US
dc.titleVulnerability of Transportation Networks to Traffic-Signal Tamperingen_US
dc.typeArticleen_US
dc.identifier.citationLaszka, Aron et al. “Vulnerability of Transportation Networks to Traffic-Signal Tampering.” 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS),11-14 April, Vienna, Austria, 2016, IEEE, 2016.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineeringen_US
dc.contributor.mitauthorAmin, Saurabh
dc.relation.journalProcceedings of the 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS)en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsLaszka, Aron; Potteiger, Bradley; Vorobeychik, Yevgeniy; Amin, Saurabh; Koutsoukos, Xenofonen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-1554-015X
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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