Abstract
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.
Reference45 articles.
1. A New Biometric Technology Based on Mouse Dynamics
2. User authentication through typing biometrics features
3. The SPEC# programming system: An overview. Construction and Analysis of Safe, Secure and Interoperable Smart devices (CASSIS) 2004;M.Barnett;LNCS,2005
4. Bleha, S. A., Knopp, J., & Obadiat, M. S. (2002). Performance of the perceptron algorithm for the classification of computer users. Proceedings of the ACM/SIGAPP Symposium on Applied Computing. New York, NY: ACM Press.