Data-driven Traffic Control and Management System Attack Pattern Discovery and Hacking Knowledge Extraction for Cyber-security Enhancement

Investigator(s):

• Roger Chen, University of Hawaii at Manoa, ORCID # 0000-0002-0528-6007 (PI)

Project Description:

The objective of the research is to develop data-driven approaches for evaluating the risk of cyber-attacks and hacking of field-side traffic management systems and, secondarily, on informing an agency’s response to an attack. We will accomplish this through a data-driven pattern discovery of attacks and hacking. The project will focus on field devices (e.g., traffic signal controllers and cabinets, dynamic message signs, V2I roadside units, weigh-in-motion systems, road-weather information systems, remote processing and sensing units, and other IP-addressable devices), field communications networks, and field-to-center communications. We summarize the major objectives of this project as follows:

Figure 1: Study Framework

1. Review existing traffic management systems and their risks and vulnerabilities for cyber-attack and hacking; the traffic management system for the City and County of Honolulu and the those for the outer islands will be examined due to their representation of different levels of resources available for each jurisdiction.
2. Propose a method for generating synthetic cyber-attack and hacking systems to support developing a model to detect these outcomes; data on both conventional normal and cyber-attack contexts are needed to train a model to identify and distinguish between the two.
3. Evaluating the proposed model and approach using real and synthetic datasets.