Data-Driven Security Measurements to Improve Safety in NYC and NJ Mass Transit
Nithya Nalluri, Michael Bsales, Christie Nelson
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Nithya Nalluri
Department of Electrical and Computer Engineering, The College of New Jersey, Ewing Township, New Jersey, United States
Michael Bsales
Department of Computer Science and Engineering and Department of Economics, University of Notre Dame, Notre Dame, Indiana, United States
Christie Nelson
DIMACS, Rutgers University, New Brunswick Rutgers, New Jersey, United States
Cite this paper as:Nalluri, N., Bsales, M., Nelson, C. (2023). Data-Driven Security Measurements to Improve Safety in NYC and NJ Mass Transit.
Journal of Systemics, Cybernetics and Informatics, 21(3), 47-55. https://doi.org/10.54808/JSCI.21.03.47
Online ISSN (Journal): 1690-4524
Abstract
Public transit in America in recent years is potentially vulnerable to terrorist or mass casualty attacks. These vulnerabilities are in part due to the lack of strict screening and content policing, unlike security at airports, but also their attractiveness as a potentially high-value target. Although current public transit systems are designed to efficiently allow passengers to quickly travel, screening of individual riders for weapons remains limited due to current technology limitations and high peak throughput requirements. This paper aims to develop an understanding of the current state of security check systems as applicable to high-traffic subway stations. We also worked towards creating a proof-of-concept risk analysis model using crime and other types of publicly available data for the New York City and New Jersey transit regions.
