Vulnerability of Transportation Networks to Traffic-Signal Tampering
Aron Laszka, Bradley Potteiger, Yevgeniy Vorobeychik, Saurabh Amin, Xenofon Koutsoukos

Citation
Aron Laszka, Bradley Potteiger, Yevgeniy Vorobeychik, Saurabh Amin, Xenofon Koutsoukos. "Vulnerability of Transportation Networks to Traffic-Signal Tampering". 7th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), April, 2016.

Abstract
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.

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Citation formats

• HTML

  Aron Laszka, Bradley Potteiger, Yevgeniy Vorobeychik,
  Saurabh Amin, Xenofon Koutsoukos. <a
  href="http://www.cps-forces.org/pubs/115.html"
  >Vulnerability of Transportation Networks to
  Traffic-Signal Tampering</a>, 7th ACM/IEEE
  International Conference on Cyber-Physical Systems (ICCPS),
  April, 2016.

• Plain text

  Aron Laszka, Bradley Potteiger, Yevgeniy Vorobeychik,
  Saurabh Amin, Xenofon Koutsoukos. "Vulnerability of
  Transportation Networks to Traffic-Signal Tampering".
  7th ACM/IEEE International Conference on Cyber-Physical
  Systems (ICCPS), April, 2016.

• BibTeX

  @inproceedings{LaszkaPotteigerVorobeychikAminKoutsoukos16_VulnerabilityOfTransportationNetworksToTrafficSignal,
      author = {Aron Laszka and Bradley Potteiger and Yevgeniy
                Vorobeychik and Saurabh Amin and Xenofon Koutsoukos},
      title = {Vulnerability of Transportation Networks to
                Traffic-Signal Tampering},
      booktitle = {7th ACM/IEEE International Conference on
                Cyber-Physical Systems (ICCPS)},
      month = {April},
      year = {2016},
      abstract = {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.},
      URL = {http://cps-forces.org/pubs/115.html}
  }
  

Posted by Aron Laszka on 15 Mar 2016.
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