Abstract
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.
Highlights
Modern smartphones usually employ one or a combination of the following methods to validate the identity of the user: PIN, password, pattern, fingerprint sensor, or facial recognition
The present paper focuses on the potential architecture of a continuous gait recognition mechanism which runs in the background on an Android smartphone
It can be observed that all walking-related activities have high accuracy scores, which is encouraging for our gait detection-based authentication method
Summary
Modern smartphones usually employ one or a combination of the following methods to validate the identity of the user: PIN, password, pattern, fingerprint sensor, or facial recognition. These five mechanisms can be grouped into two categories based on which factor they represent in the three-factor authentication model (https://blog.gemalto.com/security/2011/09/05/three-factor-authenticationsomething-you-know-something-you-have-something-you-are/). The first three methods are based on something known and are usually created by the user. The main issue of these approaches is the human factor, the education of the user regarding cybersecurity being decisive in the strength of the password. The large number of passwords a user has to remember leads to duplicate and low-strength passwords. Using something owned by the user may enhance these methods, but implies using an additional software product (e.g., soft token) or physical device (e.g., hard token)
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