Developing Secure Strategies for Vehicular Ad hoc Networks in Connected and Autonomous Vehicles
This research aims at developing a resilient framework to be applied to transportation systems using connected and autonomous vehicles (CAVs). This responds to vehicular accident rates often related to inefficient communication systems. A Vehicular Ad hoc Network (VANET) is a significant innovation toward avoiding such deadly traffic mishaps with the assistance of a variety of state-of-the-art safety applications. A VANET is a self-organized, multi-purpose, service-oriented communication network enabling vehicle-to-vehicle and vehicle-to-roadside infrastructure communication for the purpose of exchanging messages to ensure an efficient and comfortable traffic system on roads. Its value, however, can potentially be impaired by cyberattacks. In particular, the focus of this research will be on false data injection attacks, in which a malicious agent aims at affecting CAV behavior by injecting in the network false information concerning, for example, the traffic condition in the area or the availability of charging stations for the CAVs. The countermeasures will be developed using anomaly identification techniques based on learning and detection algorithms. In particular, the data collected from the nearby CAVs will be utilized to simulate and estimate the time evolution of the system; based on the outcome of such simulation, the CAV will apply a decision logic to distinguish between useful information and malicious data. In summary the approach aims at developing security game frameworks for vehicular networks, that model the interaction between malicious attackers to VANETs and various defense mechanisms protecting them. Mitigation measures will be applied emphasizing multi-modal connectivity involving CAVs and/or traditional vehicles. This connectivity introduces flexibility in transport options. Such flexibility also captures similar concepts for communication and information technologies such as redundant sensors and various kinds of backup systems and countermeasures, and connections to other modes. This research is designed to provide guidance for users and developers of safe vehicular systems.
Language
- English
Project
- Status: Completed
- Funding: $90000
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Contract Numbers:
69A3551747124
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Connected Cities for Smart Mobility towards Accessible and Resilient Transportation Center (C2SMART)
New York University
Tandon School of Engineering
Brooklyn, NY United States -
Performing Organizations:
Connected Cities for Smart Mobility towards Accessible and Resilient Transportation Center (C2SMART)
New York University
Tandon School of Engineering
Brooklyn, NY United StatesNew York University Tandon School of Engineering
6 Metrotech Center
Brooklyn, NY United States 11201 -
Principal Investigators:
Zhu, Quanyan
- Start Date: 20190301
- Expected Completion Date: 20200531
- Actual Completion Date: 20200531
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Algorithms; Autonomous vehicles; Computer security; Connected vehicles; Countermeasures; Simulation; Traffic safety; Vehicle to infrastructure communications; Vehicle to vehicle communications; Vehicular ad hoc networks
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01705186
- Record Type: Research project
- Source Agency: Connected Cities for Smart Mobility towards Accessible and Resilient Transportation Center (C2SMART)
- Contract Numbers: 69A3551747124
- Files: UTC, RIP
- Created Date: May 22 2019 1:15PM