Secure Continuous Biometric-Enhanced Authentication

Klosterman, Andrew J.; Ganger, Gregory R.

doi:10.21236/ada382238

Cited by 34 publications

(9 citation statements)

References 18 publications

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“…A number of studies on continuous user authentication have been published [7]- [14]. These schemes typically use one or more primary (hard) biometric traits (e.g., fingerprint or face).…”

Section: Introductionmentioning

confidence: 99%

Soft Biometric Traits for Continuous User Authentication

Niinuma

Park

Jain

2010

IEEE Trans.Inform.Forensic Secur.

177

112

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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.

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“…A number of studies on continuous user authentication have been published [7]- [14]. These schemes typically use one or more primary (hard) biometric traits (e.g., fingerprint or face).…”

Section: Introductionmentioning

confidence: 99%

Soft Biometric Traits for Continuous User Authentication

Niinuma

Park

Jain

2010

IEEE Trans.Inform.Forensic Secur.

177

112

View full text Add to dashboard Cite

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“…• Support for multiple users sharing a certain account; this may require a biometric hand-off [4] to occur between users.…”

Section: Resultsmentioning

confidence: 99%

“…The study conducted by Klosterman et al [4] in the design of biometric-enhanced authentication system describes the challenges posed by such a system. It points out that for unobtrusive continuous monitoring of a user's biometric traits, the choice of trait should be such that it does not hinder the user from working.…”

Section: Related Workmentioning

confidence: 99%

Continuous multimodal user authentication: coupling hard and soft biometrics with support vector machines to attenuate noise

Srinivasa

Gosukonda

2014

CSIT

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Static Authentication provides a secure framework for a one-time authentication session, but fails to authenticate the user throughout the session. This presents the possibility of an imposter gaining access when a user session is active and the user moves away from the system. The goal of continuous authentication is to authenticate the user right from the initial stages of log-in till log-out. Intuitively, this can be implemented by extrapolating the tried-and-tested static authentication techniques throughout the session. However, extrapolating one-time authentication techniques poses new challenges of being computationally expensive, restricting the user's movement and postures in front of the system, depending on extra expensive hardware and deviating the user from his workflow. In these situations, the user no longer remains uninterrupted by the authentication process in the background. The proposed framework provides unobtrusive Continuous Authentication, by alternating between two modes which utilize hard and soft biometrics respectively, depending on certain confidence parameters. We use facial features as the hard biometric trait for recognizing the user. Employing face recognition for extended periods of time produces noise, which is dampened by using a supervised machine learning algorithm. The color of user's clothing as the soft biometric trait relieves the CPU of comparatively high computation and relaxes constraints on the user's upper body movement.

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“…Therefore, person verification should be carried out continuously until the end of the exam. Some older studies claim that continuous authentication leads to high computational cost [7], but fortunately, computers nowadays have much higher performance than ten years ago. Furthermore, it is not necessary to perform authentication checks at extremely short intervals.…”

Section: Using Touch Gestures For Authenticationmentioning

confidence: 99%

Hand Shape Discrimination in Touch Interface toward Personal Authentication on a Tablet Computer

Ogata

Sakamoto

Takei

et al. 2013

2013 International Conference on Biometrics and Kansei Engineering

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Recently, e-assessment has become popular, and it is now technically possible for people to take exams at home. However, because the testing environment is dramatically different from the traditional one, new technologies are required to prevent cheating. Many studies have addressed testing environments where a keyboard and mouse are used as input devices, but few have focused on an environment using tablet computers, which are widespread nowadays. The aim of our study is to develop a method of detecting impersonation using touch gestures on a tablet computer. We verified that tap gestures performed by different people on a tablet computer can be distinguished by extracting some features from finger tapping images. An experiment using 30 subjects was conducted for verification.

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Secure Continuous Biometric-Enhanced Authentication

Cited by 34 publications

References 18 publications

Soft Biometric Traits for Continuous User Authentication

Soft Biometric Traits for Continuous User Authentication

Continuous multimodal user authentication: coupling hard and soft biometrics with support vector machines to attenuate noise

Hand Shape Discrimination in Touch Interface toward Personal Authentication on a Tablet Computer

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