Latent semantic analysis and keyword extraction for phishing classification

Authors: Gastón L'Huillier, A.H., Richard Weber, and Sebastián A. 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 naive 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.

Ref: In Proceedings of the IEEE International Conference on Intelligence and Security Informatics (ISI 2010), Vancouver, BC, Canada, May 23-26, IEEE Press 2010.

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