Performance and security analysis of Gait-based user authentication

Verifying the identity of a user, usually referred to as user authentication, before granting access to the services or objects is a very important step in many applications. People pass through some sorts of authentication process in their daily life. For example, to prove having access to the computer the user is required to know a password. Similarly, to be able to activate a mobile phone the owner has to know its PIN code, etc. Some user authentication techniques are based on human physiological or behavioral characteristics such as fingerprints, face, iris and so on. Authentication methods differ in their advantages and disadvantages, e.g. PIN codes and passwords have to be remembered, eye-glasses must be taken off for face authentication, etc. Security and usability are important aspects of user authentication. The usability aspect relates to the unobtrusiveness, convenience and user-friendliness of the authentication technique. Security is related to the robustness of the authentication method against attacks. Recent advances in electronic chip development offer new opportunities for person authentication based on his gait (walking style) using small, light and cheap sensors. One of the primary advantages of this approach is that it enables unobtrusive user authentication. Although studies on human recognition based on gait indicate encouraging performances, the security per se (i.e. robustness and/or vulnerability) of gait-based recognition systems has received little or no attention. The overall goal of the work presented in this thesis is on performance and security analysis of gait-based user authentication. The nature of the contributions is not on developing novel algorithms, but rather on enhancing existing approaches in gait-based recognition using small and wearable sensors, and developing new knowledge on security and uniqueness of gait. The three main research questions addressed in this thesis are: (1) What are the performances of recognition methods that are based on the motion of particular body parts during gait? (2) How robust is the gait-based user authentication? (3) What aspects do influence the uniqueness of human gait? In respect to the first research question, the thesis identifies several locations on the body of the person, whose motion during gait can provide identity information. These body parts include hip, trouser pockets, arm and ankle. Analysis of acceleration signals indicates that movements of these body segments have some discriminative power. This might make these modalities suitable as an additional factor in multi-factor authentica-