An Eye Opener on the Use of Machine Learning in Eye Movement Based Authentication

Peng, Siyuan; Madi, Naser Al

doi:10.1145/3517031.3531631

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Behavioral Biometrics Eye Tracking Sensors1

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2024

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Cited by 2 publications

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“…Peng et al [131] focused on incorporating linguistic features into eye movement-based authentication. They used an eye movement dataset collected from participants performing poem reading tasks in the Gazebase database used in [124,125].…”

Section: Behavioral Biometrics Eye Tracking Sensorsmentioning

confidence: 99%

Recent Trends of Authentication Methods in Extended Reality: A Survey

Hallal,

Rhinelander,

Venkat

2024

ASI

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Extended Reality (XR) is increasingly gaining momentum in industries such as retail, health, and education. To protect users’ personal data, establishing a secure authentication system for XR devices becomes essential. Recently, the focus on authentication methods for XR devices has been limited. To further our understanding of this topic, we surveyed authentication schemes, particularly systems and methods deployed in XR settings. In this survey, we focused on reviewing and evaluating papers published during the last decade (between 2014 and 2023). We compared knowledge-based authentication, physical biometrics, behavioral biometrics, and multi-model methods in terms of accuracy, security, and usability. We also highlighted the benefits and drawbacks of those methods. These highlights will direct future Human–computer Interaction (HCI) and security research to develop secure, reliable, and practical authentication systems.

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Section: Behavioral Biometrics Eye Tracking Sensorsmentioning

confidence: 99%