Continuous Implicit Authentication through Touch Traces Modelling

• Published in: 2020 IEEE 20th International Conference on Software Quality, Reliability and Security (QRS) pp. 111 - 120
• Main Authors: Karanikiotis, Thomas, Papamichail, Michail D., Chatzidimitriou, Kyriakos C., Oikonomou, Napoleon-Christos I., Symeonidis, Andreas L., Saripalle, Sashi K.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-12-2020
• Subjects: Authentication; Implicit Authentication; Security; Smartphone Security; Software quality; Software reliability; Support vector machines; Task analysis; Touch Traces Modelling; Usability
• DOI: 10.1109/QRS51102.2020.00026

Nowadays, the continuously increasing use of smart-phones as the primary way of dealing with day-to-day tasks raises several concerns mainly focusing on privacy and security. In this context and given the known limitations and deficiencies of traditional authentication mechanisms, a lot of research efforts are targeted towards continuous implicit authentication on the basis of behavioral biometrics. In this work, we propose a methodology towards continuous implicit authentication that refrains from the limitations imposed by small-scale and/or controlled environment experiments by employing a real-world application used widely by a large number of individuals. Upon constructing our models using Support Vector Machines, we introduce a confidence-based methodology, in order to strengthen the effectiveness and the efficiency of our approach. The evaluation of our methodology on a set of diverse scenarios indicates that our approach achieves good results both in terms of efficiency and usability.