Soft Biometric Traits for Continuous User Authentication

Abstract

Abstract-Most existing computer and network systems authenticate a user only at the initial login session. This could be a critical security weakness, especially for high-security systems because it enables an impostor to access the system resources until the initial user logs out. This situation is encountered when the logged in user takes a short break without logging out or an impostor coerces the valid user to allow access to the system. To address this security flaw, we propose a continuous authentication scheme that continuously monitors and authenticates the logged in user. Previous methods for continuous authentication primarily used hard biometric traits, specifically fingerprint and face to continuously authenticate the initial logged in user. However, the use of these biometric traits is not only inconvenient to the user, but is also not always feasible due to the user's posture in front of the sensor. To mitigate this problem, we propose a new framework for continuous user authentication that primarily uses soft biometric traits (e.g., color of user's clothing and facial skin). The proposed framework automatically registers (enrolls) soft biometric traits every time the user logs in and fuses soft biometric matching with the conventional authentication schemes, namely password and face biometric. The proposed scheme has high tolerance to the user's posture in front of the computer system. Experimental results show the effectiveness of the proposed method for continuous user authentication.

Biometric Authentication

“…In the categorical matrix, traits relating to head coverage (2) and (4) are highly correlated, as are the traits (15) and (18) relating to the description of items attached to the body. Clothing categories are well correlated for upper (5) and lower (9) body, as expected. In the comparative matrix, sleeve length (8) and heel level (14) are highly correlated.…”

“…The capability of verbal retrieval from images and videos can pave the way for applications that can search surveillance data of a crime scene to match people to potential suspects described verbally by eyewitnesses. Soft biometric databases based on categorical labels can be incorporated with other biometrics to enhance recognition, such as integrating soft body traits with a gait signature [4], and using soft facial traits along with other (hard) facial traits [5]. Nevertheless, soft comparative labels have been demonstrated to be more successful in representing the slight differences between people in bodily descriptions [1].…”

“…There are few research studies associated with using clothing for biometric purposes [2,5,9,11,12]. The majority of existing research employs computer vision algorithms and machine learning techniques to extract and use visual clothing descriptions in applications including: online person recognition [5,11]; semantic attributes for re-identification [13]; detecting and analysing semantic descriptions (labels) of clothing colours and types to supplement other bodily and facial soft attributes in automatic search and retrieval [9]; and utilizing some clothing attributes like colour [14] and style to improve the observation and retrieval at a distance in surveillance environments [2]. Even with images captured on different days, there remains sufficient information to compare and establish identity, since clothes are often re-worn or a particular individual may prefers a specific clothing style or colour [15].…”

Facial soft biometric features for forensic face recognition

“…The average width of each eyebrow (10-11) and the mouth height (22) follow the same concept by the estimation of the upper and bottom contour of each facial trait and the calculation of the average distance across all vertical parallel segments. Finally, the chin width (26), uses the estimated landmarks (c 4 and c 5 ) for the estimation of the average distance across all the horizontal parallel segments between the right and left limits of the face.…”

“…Niinuma et al [26] proposed a new framework for continuous user authentication that primarily uses soft biometric traits (e.g., color of user's clothing and facial skin), scheme that continuously monitors and authenticates the logged in user. Other recent publications used comparative human descriptions for facial identification, e.g.…”