%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2019/09.13.16.38
%2 sid.inpe.br/sibgrapi/2019/09.13.16.38.06
%@doi 10.1109/SIBGRAPI.2019.00038
%T PursuitPass: A Visual Pursuit-Based User Authentication System
%D 2019
%A Carneiro, Alex Torquato Souza,
%A Elmadjian, Carlos Eduardo Leão,
%A Gonzales, Candy Veronica Tenorio,
%A Coutinho, Flavio Luiz,
%A Morimoto, Carlos Hitoshi,
%@affiliation University of São Paulo
%@affiliation University of São Paulo
%@affiliation University of São Paulo
%@affiliation University of São Paulo
%@affiliation University of São Paulo
%E Oliveira, Luciano Rebouças de,
%E Sarder, Pinaki,
%E Lage, Marcos,
%E Sadlo, Filip,
%B Conference on Graphics, Patterns and Images, 32 (SIBGRAPI)
%C Rio de Janeiro, RJ, Brazil
%8 28-31 Oct. 2019
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K smooth pursuit, pattern recognition, security.
%X As our lives get more deeply submerged in digital format, ubiquitous access to sensitive data requires more secure and efficient user authentication procedures. Methods that solely relied on password entry were lately enhanced with the use of biometrics. Yet, these techniques can still be tricked by, for example, recordings of the face, voice, and fingerprint cloning. In this paper we introduce PursuitPass, a compact, robust, and efficient visual pursuit-based authentication system. PursuitPass is a user calibration-free method that requires the user to enter a password by visually pursuing moving targets on a small screen, such as a public ATM or a personal mobile phone. Because eye movements are used as input, passwords are better protected against shoulder surfing. Also, since targets can potentially move in unpredictable ways, it naturally imposes a liveness feature that cannot be counterfeited by recordings of the eyes. We investigated four pattern-matching algorithms to match visual pursuit user data with the movement of the targets. Two experiments were conducted. The first experiment aimed to define the best performing matching algorithm and configuration for PursuitPass. The second experiment aimed to evaluate the performance of our prototype. PursuitPass achieved a 96.82% accuracy with an average time of 10.42 s on a series of 4-digit PIN entry trials.
%@language en
%3 camera_ready_71.pdf