Keystroke Dynamics Based Authentication Using Possibilistic Renyi Entropy Features and Composite Fuzzy Classifier

作     者：Aparna Bhatia Madasu Hanmandlu 

作者机构：Department of Electrical Engineering Indian Institute of Technology Delhi HauzKhas New Delhi India CSE Department MVSR Engg. College Nadergul Hyderabad Formally with EE Department IIT Delhi New Delhi 

出 版 物：《Journal of Modern Physics》 (现代物理（英文）)

年 卷 期：2018年第9卷第2期

页      面：112-129页

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Keystroke Dynamics Information Set Renyi Entropy Function and Its Possibilistic Version Composite Fuzzy Classifier 

摘      要：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.