@InProceedings{CarneiroElmGonCouMor:2019:ViPuUs,
               author = "Carneiro, Alex Torquato Souza and Elmadjian, Carlos Eduardo 
                         Le{\~a}o and Gonzales, Candy Veronica Tenorio and Coutinho, 
                         Flavio Luiz and Morimoto, Carlos Hitoshi",
          affiliation = "{University of S{\~a}o Paulo} and {University of S{\~a}o Paulo} 
                         and {University of S{\~a}o Paulo} and {University of S{\~a}o 
                         Paulo} and {University of S{\~a}o Paulo}",
                title = "PursuitPass: A Visual Pursuit-Based User Authentication System",
            booktitle = "Proceedings...",
                 year = "2019",
               editor = "Oliveira, Luciano Rebou{\c{c}}as de and Sarder, Pinaki and Lage, 
                         Marcos and Sadlo, Filip",
         organization = "Conference on Graphics, Patterns and Images, 32. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "smooth pursuit, pattern recognition, security.",
             abstract = "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.",
  conference-location = "Rio de Janeiro, RJ, Brazil",
      conference-year = "28-31 Oct. 2019",
                  doi = "10.1109/SIBGRAPI.2019.00038",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2019.00038",
             language = "en",
                  ibi = "8JMKD3MGPEW34M/3U38PNP",
                  url = "http://urlib.net/ibi/8JMKD3MGPEW34M/3U38PNP",
           targetfile = "camera_ready_71.pdf",
        urlaccessdate = "2024, Apr. 27"
}