Terrorist detection system

Yuval Elovici, Abraham Kandel, Mark Last, Bracha Shapira, Omer Zaafrany, Moti Schneider, Menahem Friedman

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

Terrorist Detection System (TDS) is aimed at detecting suspicious users on the Internet by the content of information they access. TDS consists of two main modules: a training module activated in batch mode, and an on-line detection module. The training module is provided with web pages that include terror related content and learns the typical interests of terrorists by applying data mining algorithms to the training data. The detection module performs real-time monitoring on users' traffic and analyzes the content of the pages they access. An alarm is issued upon detection of a user whose content of accessed pages is "too" similar to typical terrorist content. TDS feasibility was tested in a network environment. Its detection rate was better than the rate of a state of the art Intrusion Detection System based on anomaly detection.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsJean-Francois Boulicaut, Floriana Esposito, Fosca Giannotti, Dino Pedreschi
PublisherSpringer Verlag
Pages540-542
Number of pages3
ISBN (Print)3540231080, 9783540231080
DOIs
StatePublished - 1 Jan 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3202
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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