期刊名称：Oriental Journal of Computer Science and Technology
印刷版ISSN：0974-6471
出版年度：2010
卷号：3
期号：2
页码：331-336
语种：English
出版社：Oriental Scientific Publishing Company
摘要：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. In this Paper we present an Neural based Self organization map algorithm in TDS, where the detection algorithm was enhanced to improve the detection and reduce the false alarms in Terrorist Detection System.
关键词：Terrorist detection system ; neural network ; data mining
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