Author(s)

Aparna Bhatia^1*, Madasu Hanmandlu²

¹Department of Electrical Engineering, Indian Institute of Technology Delhi, HauzKhas, New Delhi, India.
²CSE Department, MVSR Engg. College, Nadergul, Hyderabad, Formally with EE Department, IIT Delhi, New Delhi.

This paper presents the formulation of the possibilistic Renyi entropy function from the Renyi entropy function using the framework of Hanman-Anirban entropy function. The new entropy function is used to derive the information set features from keystroke dynamics for the authentication of users. A new composite fuzzy classifier is also proposed based on Mamta-Hanman entropy function and applied on the Information Set based features. A comparison of the results of the proposed approach with those of Support Vector Machine and Random Forest classifier shows that the new classifier outperforms the other two.

Keystroke Dynamics, Information Set, Renyi Entropy Function and Its Possibilistic Version, Composite Fuzzy Classifier

Bhatia, A. and Hanmandlu, M. (2018) Keystroke Dynamics Based Authentication Using Possibilistic Renyi Entropy Features and Composite Fuzzy Classifier. Journal of Modern Physics, 9, 112-129. doi: 10.4236/jmp.2018.92008.