Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

VIT Unitversity

Department of Database Systems

School of Computer Science and Engineering

Vellore Campus

Innovations in Computer Science and Engineering Lecture Notes in Networks and Systems

A Hybrid Feature Selection Approach for Handling a High-Dimensional Data

Fulltext

Procedia Computer Science

Clustering West Nile Virus Spatio-temporal data using ST-DBSCAN

Designing for a Digital and Globalized World Lecture Notes in Computer Science

Dengue Prediction Using Hierarchical Clustering Methods

Knowledge-based user authentication technique is a common and easy access control mechanism. But people are uninspired while choosing a healthy password or PIN. It increases the probability of guessing attacks. In this situation, to minimize these attacks, keystroke dynamics is a good choice; here users are not only identified by the password but their typing style is also accounted for. Keystroke dynamics is the method of analyzing typing pattern on a computer keyboard or touch screen and classifying the users based on their regular typing rhythm. It is a behavioral biometric characteristic which we have learned in our life and relates to the issues in human identification/authentication. This is the method where people can be identified by their typing style similar to hand writing or voice print. Being noninvasive and cost-effective, this method is a good field of research. But the performance of keystroke dynamics is less than other popular morphological biometric characteristics like face print, iris, and finger print recognition due to high rate of intraclass variation or high Failure to Enroll Rate (FER). So, this technique demands higher level of security. In this chapter, we are interested in investigating the integration of the soft biometric features, gender and age group, with the existing keystroke dynamics user authentication systems proposed by [1-3]. © 2018 by Taylor & Francis Group, LLC.

GENERAL

Department of Biotechnology

School of Bio Sciences and Technology

World University root node

Internet of Things (IoT): Technologies, Applications, Challenges and Solutions

User authentication: Keystroke dynamics with soft biometric features

2015 IEEE International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)

A modified brainstorm optimization for clustering using hard c-means

Network Security and Types of Attacks in Network