Bimodal Keystroke Dynamics-Based Authentication for Mobile Application Using Anagram

Currently, most of the smartphones recognize uses based on static biometrics, such as face and fingerprint. However, those traits were vulnerable against spoofing attack. For overcoming this problem, dynamic biometrics like keystroke gaze are introduced since it is more resistant This research focuses dynamics for strengthening user recognition system attacks. recognizing a user, keystrokes feature used in login process compared with features stored database. evaluating accuracy proposed system, words generated Indonesian anagram used. Furthermore, conducting experiment, 34 participants asked to type set using smartphone keyboard. Then, each user’s recorded. The consists latency digraph which extracted from record. According experiment result, error method decreased by 23.075% EER FAR FRR 16.381% 10.41% respectively, Kim’s method. It means that successful increase performance reducing rates