Biometric Authentication Based on Touchscreen Swipe Patterns. (2016)

• Record Type: Journal Article
• Authors: Antal, Margit; Szabó, László Zsolt
• Is Part Of: Procedia technology. Volume 22(2016)
• Page Start: 862
• Page End: 869
• Publication Date: 2016
• Subjects: Security -- Authentication -- Behavioral Biometrics -- Touchscreen -- Swipe -- Eysenck Personality Questionnaire; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.01.061
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: In this work we investigated user authentication on mobile devices using touch behavior and micro movements of the device. The novelty of our work lies in the collection of user behavior data during the filling in of a psychological questionnaire (implemented as an Android application). In order to answer the questions, users were required to use a slider. Therefore users were constrained to using only straight horizontal swipes. Extensive evaluations were conducted on the resulting dataset using one- and two-class classification algorithms. Although authentication EER based on single swipe is around 4%, this was improved by using sequences of 5 swipes (0.2% EER). Features related to micro movement of the device proved to be the most discriminating ones.