Manjula R

Department of Software Systems

School of Computer Science and Engineering

Vellore Campus

N. Muni Kumar

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

Design of Multi-layer Perceptron for the Diagnosis of Diabetes Mellitus Using Keras in Deep Learning

Smart Intelligent Computing and Applications Smart Innovation, Systems and Technologies

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.

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

User authentication: Keystroke dynamics with soft biometric features

2017 International Conference on Electrical, Computer and Communication Engineering (ECCE)

An expert clinical decision support system to predict disease using classification techniques

2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

Comparative risk analysis on prediction of Diabetes Mellitus using machine learning approach

2016 Fourth International Conference on Parallel, Distributed and Grid Computing (PDGC)

A first attempt to develop a diabetes prediction method based on different global datasets

2015 IEEE Recent Advances in Intelligent Computational Systems (RAICS)

Prediction and diagnosis of diabetes mellitus — A machine learning approach

Journal	Data powered by TypesetSmart Intelligent Computing and Applications Smart Innovation, Systems and Technologies
Publisher	Data powered by TypesetSpringer Singapore
ISSN	2190-3018
Open Access	0