Towards Continuous Authentication Based on Gait Using Wearable Motion Recording Sensors

Towards Continuous Authentication Based on Gait Using Wearable Motion Recording Sensors

Mohammad Omar Derawi, Davrondzhon Gafurov, Patrick Bours
DOI: 10.4018/978-1-4666-2919-6.ch076
(Individual Chapters)
No Current Special Offers


In this chapter we present continuous authentication using gait biometric. Gait is a person’s manner of walking and gait recognition refers to the identification and verification of an individual based on gait. This chapter discusses advantages and disadvantages of gait biometrics in the context of continuous authentication. Furthermore, we present a framework for continuous authentication using gait biometrics. The proposed framework extends on traditional static (one-time) user authentication. The framework can also be applied to other biometric modalities with small modifications.
Chapter Preview


A particular way or manner of moving on foot is a definition for gait (Farlex). Every person has his or her own way of walking. From early medical studies it appears that there are twenty-four different components to human gait, and that if all the measurements are considered, gait is unique (BenAbdelkader, et al., 2001). This has made gait recognition an interesting topic to be used for identifying individuals by the manner in which they walk. Figure 1 illustrates the complex biological process of the musculo-skeletal system, which can be divided into several types of sub events of human-gait. The instances that are shown in this figure are used to extract parameters for being used as an identification system of each individual.

Figure 1.

Division of the gait cycle into five stance phase periods and two swing phase periods (Adapted from (Sminchisescu, et al., 2004))


The analysis of biometric gait recognition has been studied for a longer period of time (Larsen, et al., 2008; Nixon, et al., 2002; Nixon, et al., 2005; Niyogi & Adelson, 1994; Wang, et al., 2003) for the use in identification, surveillance and forensic systems and is becoming important, since it can provide more reliable and efficient means of identity verification.

Today, computer systems demand authentication in case of using the system. Typically, the authentication is performed at login time either with a password, token, biometric characteristic and/or a combination of these. Performing the last mentioned might give further guarantee that the claimed user logging in is the authorized user instead of a burglar. However, once the user has been granted access; most systems assume that the user is continuously legitimated into the system.

In critical or high security environments, it should be ensured that the user must be the legitimated throughout usage. Therefore, user authentication needs to be performed in a continuous way within the time the system is actively being used. Furthermore, authentication needs to be “attractive” for the user. This means that in the authentication process the users do not need to do anything special, like for example periodically entering a password. Continuous authentication using biometrics can fit these needs. Thus, one of the important requirements in continuous authentication is unobtrusiveness, since this can be monitored in a non-intrusive way. The Wearable Sensor (WS) based method can be a very good candidate to fulfill this requirement, compared to current knowledge-based mechanisms.

This chapter is structured as follows: Section ‘Background’ gives the state of the art overview of gait recognition and activity recognition. Section ‘Evaluation of a Biometric System’ introduces the definition of static and continuous authentication. The next section introduces the biometric continuous authentication (CA) system using gait recognition. This is the major contribution in this chapter and discusses CA using gait. The last section concludes the paper and gives a description on how wearable gait recognition can be improved by proposing new ideas for future work.


Background / State Of The Art

This section is divided into 2 subsections. First subsection describes the motion-based (gait biometrics) identity verification. Second subsection introduces activity recognition.

Complete Chapter List

Search this Book: