Gait Recognition as an Authentication Method for Mobile Devices

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 15; p. 4110
• Main Authors: Axente, Matei-Sorin, Dobre, Ciprian, Ciobanu, Radu-Ioan, Purnichescu-Purtan, Raluca
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 23.07.2020; MDPI
• Subjects: Accelerometers; Algorithms; Authentication; Computer Security; Confidence; Datasets; Facial recognition technology; Gait; gait detection; Gait recognition; Humans; Methods; mobile devices; Motion sensors; Privacy; Sensors; Smartphone; Smartphones; Statistical analysis; Statistical models; mobile devices; privacy; smartphones; authentication; gait detection
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s20154110

With the rate at which smartphones are currently evolving, more and more of human life will be contained in these devices. At a time when data privacy is extremely important, it is crucial to protect one's mobile device. In this paper, we propose a new non-intrusive gait recognition based mechanism that can enhance the security of smartphones by rapidly identifying users with a high degree of confidence and securing sensitive data in case of an attack, with a focus on a potential architecture for such an algorithm for the Android environment. The motion sensors on an Android device are used to create a statistical model of a user's gait, which is later used for identification. Through experimental testing, we prove the capability of our proposed solution by correctly classifying individuals with an accuracy upwards of 90% when tested on data recorded during multiple activities. The experiments, conducted on a low sampling rate and at short time intervals, show the benefits of our solution and highlight the feasibility of an efficient gait recognition mechanism on modern smartphones.