Cart (Loading....) | Create Account
Close category search window
 

On atypical database transactions: identification of probable frauds using machine learning for user profiling

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Kokkinaki, A.I. ; Dept. of Comput. Sci., Cyprus Univ., Nicosia, Cyprus

The paper proposes a framework for deriving users' profiles of typical behaviour and detecting atypical transactions which may constitute fraudulent events or simply a change in user's behaviour. The anomaly detection problem is presented and previous attempts to address it are discussed. The proposed approach proves that individual user profiles can be constructed and provides an algorithm that derives user profiles and an algorithm to identify atypical transactions. Lower and upper bounds for the number of misclassifications are also provided. An evaluation of this approach is discussed and some issues for further research are outlined

Published in:

Knowledge and Data Engineering Exchange Workshop, 1997. Proceedings

Date of Conference:

4 Nov 1997

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.