IEDs in the dark web: lexicon expansion and genre classification

Authors:
Hsinchun Chen
Affiliations:
Artificial Intelligence Laboratory, Department of Management Information Systems, University of Arizona, Tucson, AZ
Venue:
ISI'09 Proceedings of the 2009 IEEE international conference on Intelligence and security informatics
Year:
2009

Citing 2
Cited 0

US Domestic Extremist Groups on the Web: Link and Content Analysis

IEEE Intelligent Systems
Intelligence and Security Informatics: Second Symposium on Intelligence and Security Informatics, ISI 2004, Tucson, AZ, USA, June 10-11, 2004, Proceedings (Lecture Notes in Computer Science)

Intelligence and Security Informatics: Second Symposium on Intelligence and Security Informatics, ISI 2004, Tucson, AZ, USA, June 10-11, 2004, Proceedings (Lecture Notes in Computer Science)

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Abstract

Improvised explosive device web pages represent a significant source of knowledge for security organizations. In this paper, we present significant improvements to our approach to the discovery and classification of IED related web pages in the Dark Web. We present a statistical feature ranking approach to the expansion of the keyword lexicon used to discover IED related web pages, which identified new relevant terms for inclusion. Additionally, we present an improved web page feature representation designed to better capture the structural and stylistic cues revealing of genres of communication, and a series of experiments comparing the classification performance of the new representation with our existing approach.