@inbook{f52b7c7beca740f49ba0600adb813ed0,
title = "Terrorist detection system",
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.",
author = "Yuval Elovici and Abraham Kandel and Mark Last and Bracha Shapira and Omer Zaafrany and Moti Schneider and Menahem Friedman",
year = "2004",
month = jan,
day = "1",
doi = "10.1007/978-3-540-30116-5_59",
language = "English",
isbn = "3540231080",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "540--542",
editor = "Jean-Francois Boulicaut and Floriana Esposito and Fosca Giannotti and Dino Pedreschi",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "Germany",
}