Vulnerability of Transportation Networks to Traffic-Signal Tampering
Traffic 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,...
| প্রধান লেখক: | , , , , |
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| অন্যান্য লেখক: | |
| বিন্যাস: | প্রবন্ধ |
| ভাষা: | en_US |
| প্রকাশিত: |
Institute of Electrical and Electronics Engineers (IEEE)
2017
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| অনলাইন ব্যবহার করুন: | http://hdl.handle.net/1721.1/110202 https://orcid.org/0000-0003-1554-015X |
| _version_ | 1826213165595099136 |
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| author | Laszka, Aron Potteiger, Bradley Vorobeychik, Yevgeniy Amin, Saurabh Koutsoukos, Xenofon |
| author2 | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Laszka, Aron Potteiger, Bradley Vorobeychik, Yevgeniy Amin, Saurabh Koutsoukos, Xenofon |
| author_sort | Laszka, Aron |
| collection | MIT |
| description | Traffic 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. |
| first_indexed | 2024-09-23T15:44:22Z |
| format | Article |
| id | mit-1721.1/110202 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:44:22Z |
| publishDate | 2017 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1102022022-10-02T03:48:49Z Vulnerability of Transportation Networks to Traffic-Signal Tampering Laszka, Aron Potteiger, Bradley Vorobeychik, Yevgeniy Amin, Saurabh Koutsoukos, Xenofon Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Amin, Saurabh Traffic 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. National Science Foundation (U.S.) (Award CNS-1238959) National Science Foundation (U.S.) (Award CNS-1238962) National Science Foundation (U.S.) (Award CNS- 1239054) National Science Foundation (U.S.) (Award CNS-1239166) United States. Air Force. Research Laboratory (Award FA8750-14-2-0180) Sandia National Laboratories 2017-06-23T13:54:21Z 2017-06-23T13:54:21Z 2016-05 2016-04 Article http://purl.org/eprint/type/ConferencePaper 978-1-5090-1772-0 http://hdl.handle.net/1721.1/110202 Laszka, 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. https://orcid.org/0000-0003-1554-015X en_US http://dx.doi.org/10.1109/ICCPS.2016.7479122 Procceedings of the 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS) Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) Other repository |
| spellingShingle | Laszka, Aron Potteiger, Bradley Vorobeychik, Yevgeniy Amin, Saurabh Koutsoukos, Xenofon Vulnerability of Transportation Networks to Traffic-Signal Tampering |
| title | Vulnerability of Transportation Networks to Traffic-Signal Tampering |
| title_full | Vulnerability of Transportation Networks to Traffic-Signal Tampering |
| title_fullStr | Vulnerability of Transportation Networks to Traffic-Signal Tampering |
| title_full_unstemmed | Vulnerability of Transportation Networks to Traffic-Signal Tampering |
| title_short | Vulnerability of Transportation Networks to Traffic-Signal Tampering |
| title_sort | vulnerability of transportation networks to traffic signal tampering |
| url | http://hdl.handle.net/1721.1/110202 https://orcid.org/0000-0003-1554-015X |
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