AuthenticTap: A Behavioral Biometric Tap-Based User Authentication Method for Mobile Application

Abstract

Significant security and privacy concerns of the use of mobile devices and mobile applications user authentication methods have been an increasing concern for mobile device users. The purpose of this study is to use the behavioral biometrics of the users, particularly the tap patterns, as an alternative approach to biometric user authentication. Using the newly developed authentication method, the study conducted two user studies. First user study addressed the appropriate tolerance rate of the method through examining all the 960 tap patterns gathered. Second user study analyzed the robustness of the method in real world scenarios. The optimum tolerance rate of the method has been found within the range of 0.02 percent to 0.06 percent. Within the range, the user authentication method is robust against the scenarios as it correctly classifies the user's tap pattern. The study provided the creation of a more robust user authentication method entirely resistant to attacks in real world scenarios that users may employ to ensure the security and privacy of their mobile devices and specifically, mobile applications. The study may help standardize behavioral biometrics as a stand-alone authentication method device which can be used in institutions and establishments.