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Modeling and Quantifying Cyber Attacks on Signalized Traffic Networks

Faculty #81
Discipline: Technology & Engineering
Subcategory: STEM Research
- Benedict College


Transportation networks are considered as one of the critical physical infrastructures for resilient cities (cyber-physical systems (CPSs)). In efforts to minimize adverse effects, agencies work with the National Highway Traffic Safety Administration of the US Department of Transportation. This paper uses a belief network-based attack modeling at signalized traffic networks under connected vehicles and intelligent signals framework. For different types of cyber attacks defined in the literature, risk areas and impact of attacks are evaluated via traffic simulations with various scenarios. Technically based on the selected metrics, risk probabilities are calculated for signal controllers. Impact of these risks on an example signalized traffic network are quantified in terms of average intersection queue lengths and delays (time spent in queue and server). In addition, effect of having redundant traffic sensing systems on intersection performance measures is also demonstrated.

Funder Acknowledgement(s): NSF Grant Nos. 1719501 and 1400991 ; U.S. Department of Homeland Security Summer Research Team Program and was conducted at Critical Infrastructure Resilience Institute, University of Illinois, Urbana-Champaign; USDOT Regional University Transportation Center for Connected Multimodal Mobility

Faculty Advisor: None Listed,

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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