Design, implementation, and assessment of a usable multi-biometric continuous authentication system

Conventional access control solutions rely on a single authentication to verify a user’s identity but do nothing to ensure the authenticated user is indeed the same person using the system afterwards. Without continuous monitoring, unauthorized individuals have an opportunity to “hijack” or “tailgate” the original user’s session. Continuous authentication attempts to remedy this security loophole. Biometrics is an attractive solution for continuous authentication as it is unobtrusive yet still highly accurate. This allows the authorized user to continue about his routine but quickly detects and blocks intruders. This chapter outlines the components of a multi-biometric based continuous authentication system. Our application employs a biometric hand-off strategy where in the first authentication step a strong biometric robustly identifies the user and then hands control to a less computationally intensive face recognition and tracking system that continuously monitors the presence of the user. Using multiple biometrics allows the system to benefit from the strengths of each modality. Since face verification accuracy degrades as more time elapses between the training stage and operation time, our proposed hand-off strategy permits continuous robust face verification with relatively simple and computationally efficient classifiers. We provide a detailed evaluation of verification performance using different pattern classification algorithms and show that the final multi-modal biometric hand-off scheme yields high verification performance.

Download Full-text

Continuous Authentication in Computers

IT Policy and Ethics ◽

10.4018/978-1-4666-2919-6.ch013 ◽

2013 ◽

pp. 268-293

Author(s):

Harini Jagadeesan ◽

Michael S. Hsiao

Keyword(s):

User Behavior ◽

Behavioral Pattern ◽

Security Issue ◽

Age Identity ◽

Internet Age ◽

Continuous Authentication ◽

System Logs ◽

Computer Based ◽

Authentication System ◽

High Degree

In the Internet age, identity theft is a major security issue because contemporary authentication systems lack adequate mechanisms to detect and prevent masquerading. This chapter discusses the current authentication systems and identifies their limitations in combating masquerading attacks. Analysis of existing authentication systems reveals the factors to be considered and the steps necessary in building a good continuous authentication system. As an example, we present a continual, non-intrusive, fast and easily deployable user re-authentication system based on behavioral biometrics. It employs a novel heuristic based on keyboard and mouse attributes to decipher the behavioral pattern of each individual user on the system. In the re-authentication process, the current behavior of user is compared with stored “expected” behavior. If user behavior deviates from expected behavior beyond an allowed threshold, system logs the user out of the current session, thereby preventing imposters from misusing the system. Experimental results show that the proposed methodology improves the accuracy of application-based and application independent systems to 96.4% and 82.2% respectively. At the end of this chapter, the reader is expected to understand the dimensions involved in creating a computer based continuous authentication system and is able to frame a robust continual re-authentication system with a high degree of accuracy.

Download Full-text

Intelligent User Profiling Based on Sensors and Location Data to Detect Intrusions on Mobile Devices

Handbook of Research on Intrusion Detection Systems - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-7998-2242-4.ch001 ◽

2020 ◽

pp. 1-25

Author(s):

Pedro Miguel Sánchez Sánchez ◽

José María Jorquera Valero ◽

Alberto Huertas Celdran ◽

Gregorio Martínez Pérez

Keyword(s):

Mobile Devices ◽

User Interaction ◽

Machine Learning Algorithms ◽

User Profiling ◽

Normal Behaviour ◽

Location Data ◽

Secure Access ◽

Continuous Authentication ◽

Promising Solution ◽

Authentication System

Continuous authentication systems are considered as a promising solution to secure access to mobile devices. Their main benefit is the improvement of the users' experience when they use the services or applications of their mobile device. Specifically, continuous authentication avoids having to remember or possess any key to access an application or service that requires authentication. In this sense, having the user authenticated permanently increases the security of the device. It also allows the user interaction with applications to be much more fluid, simple, and satisfactory. This chapter proposes a new continuous authentication system for mobile devices. The system acquires data from the device sensors and the GPS location to create a dataset that represents the user's profile or normal behaviour. Then, the proposed system uses Machine Learning algorithms based on anomaly detection to perform user identification in real time. Several experiments have been carried out to demonstrate the performance and usefulness of the proposed solution.

Download Full-text

Continuous Authentication in Computers

Continuous Authentication Using Biometrics ◽

10.4018/978-1-61350-129-0.ch003 ◽

2011 ◽

pp. 40-66 ◽

Cited By ~ 1

Author(s):

Harini Jagadeesan ◽

Michael S. Hsiao

Keyword(s):

User Behavior ◽

Behavioral Pattern ◽

Security Issue ◽

Age Identity ◽

Internet Age ◽

Continuous Authentication ◽

System Logs ◽

Computer Based ◽

Authentication System ◽

High Degree

In the Internet age, identity theft is a major security issue because contemporary authentication systems lack adequate mechanisms to detect and prevent masquerading. This chapter discusses the current authentication systems and identifies their limitations in combating masquerading attacks. Analysis of existing authentication systems reveals the factors to be considered and the steps necessary in building a good continuous authentication system. As an example, we present a continual, non-intrusive, fast and easily deployable user re-authentication system based on behavioral biometrics. It employs a novel heuristic based on keyboard and mouse attributes to decipher the behavioral pattern of each individual user on the system. In the re-authentication process, the current behavior of user is compared with stored “expected” behavior. If user behavior deviates from expected behavior beyond an allowed threshold, system logs the user out of the current session, thereby preventing imposters from misusing the system. Experimental results show that the proposed methodology improves the accuracy of application-based and application independent systems to 96.4% and 82.2% respectively. At the end of this chapter, the reader is expected to understand the dimensions involved in creating a computer based continuous authentication system and is able to frame a robust continual re-authentication system with a high degree of accuracy.

Download Full-text