Abstract
The Terrorist Detection System (TDS) is aimed at tracking down suspected terrorists by analyzing the content of information they access. TDS operates in two modes: a training mode and a detection mode. During the training mode TDS is provided with Web pages accessed by a normal group of users and computes their typical interests. During the detection mode TDS performs real-time monitoring of the traffic emanating from the monitored group of users, analyzes the content of the Web pages accessed, and issues an alarm if the access information is not within the typical interests of the group. In this paper we present an advanced version of TDS (ATDS), where the detection algorithm was enhanced to improve the performance of the basic TDS system. ATDS was implemented and evaluated in a network environment of 38 users comparing it to the performance of the basic TDS. Behavior of suspected terrorists was simulated by accessing terror related sites. The evaluation included also sensitivity analysis aimed at calibrating the settings of ATDS parameters to maximize its performance. Results are encouraging. ATDS outperformed TDS significantly and was able to reach very high detection rates when optimally tuned.
| Original language | English |
|---|---|
| Pages (from-to) | 244-255 |
| Number of pages | 12 |
| Journal | Lecture Notes in Computer Science |
| Volume | 3495 |
| DOIs | |
| State | Published - 1 Jan 2005 |
| Event | IEEE International Conference on Intelligence and Security Informatics, ISI 2005 - Atlanta, GA, United States Duration: 19 May 2005 → 20 May 2005 |
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science