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Year:: 2021
Contributor:: Lin, Dwight (Creator); Hurley, Deborah (Advisor); Brown University School of Professional Studies and Department of Computer Science (Sponsor)
Subject:: Data protection; Privacy; Privacy technology; Facial recognition
Extent:: 36 p.
DOI: https://doi.org/10.26300/k0ye-h066

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Abstract:: Facial recognition software has evolved a great deal within the past few years and its use as a security mechanism has become quite prevalent. A security value may be achieved from its application to identify persons of interest (POIs) at large scale, private events without necessarily causing undue burden to other attendees or their privacy. By combining facial recognition identification software and state-of-the-art video security systems (or CCTV), identification of persons of interests that pose a significant or credible threat or harm may be automated and enhanced to provide an additional layer of security. Implementing this technology, however, would require strict adherence to privacy and security standards. Securing facial recognition data and ensuring privacy necessitate strong privacy controls and cybersecurity measures that include notification, consent, data minimization, access control, authentication, encryption, and strict organizational policy. This research paper provides a brief overview of facial recognition capabilities and limitations, current use cases, and presents a snapshot of the regulatory environment. It explores the feasibility of a policy framework to deploy this technology at large, private events in a more privacy protective way. The goal of this paper is to explore the viability of the application of facial recognition technology to identify POIs at large, private events by examining the security benefits weighed against the costs to the event participants, the employing organization, and the necessary cybersecurity measures to ensure security and privacy.
Notes:: Executive Master in Cybersecurity (EMCS) Capstone--Brown University, 2021

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Use and Reproduction: All rights reserved
Rights: In Copyright
Restrictions on Use: All Rights Reserved

Citation

Lin, Dwight, "Using Facial Recognition to Identify Persons of Interest at Large, Private Events, While Protecting Personal Data and Privacy" (2021). Master of Science in Cybersecurity. Brown Digital Repository. Brown University Library. https://doi.org/10.26300/k0ye-h066

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Master of Science in Cybersecurity

Brown's Master of Science (ScM) in Cybersecurity is a program for professionals designed to cultivate high-demand, industry executives with the unique and critical ability to devise and execute integrated, comprehensive cybersecurity strategies. Students gain immediately applicable knowledge and, through an …
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Using Facial Recognition to Identify Persons of Interest at Large, Private Events, While Protecting Personal Data and Privacy