By Topic

Latent semantic analysis and keyword extraction for phishing classification

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
$33 $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

4 Author(s)
Gastón L'Huillier ; Department of Computer Science, University of Chile, Blanco Encalada 2120, Santiago, Chile ; Alejandro Hevia ; Richard Weber ; Sebastián Ríos

Phishing email fraud has been considered as one of the main cyber-threats over the last years. Its development has been closely related to social engineering techniques, where different fraud strategies are used to deceit a naïve email user. In this work, a latent semantic analysis and text mining methodology is proposed for the characterisation of such strategies, and further classification using supervised learning algorithms. Results obtained showed that the feature set obtained in this work is competitive against previous phishing feature extraction methodologies, achieving promising results over different benchmark machine learning classification techniques.

Published in:

Intelligence and Security Informatics (ISI), 2010 IEEE International Conference on

Date of Conference:

23-26 May 2010