Terrorist Web Mining generates the novel information which can be used by SNA tools for Terrorist Network Mining. We assume that information available on open source media such as media reports, press reports etc can be used to draw a sociogram of these terrorist organizations. These sociograms can be used to study the relationships and roles of these terrorist organizations. In this article we propose architecture for a Terrorist Web Miner (TWM) which will search different search engines for terrorist attack information and the found web pages will be parsed for useful links. These links of the web pages which have relevant information then these web pages are stored and rank will be allocated to them. This links can farther be used for TNM.

Search engines are designed to make searching the enormous internet data easy but this digital data is growing exponentionally every year. Individual search engine can hardly cope up with this growth rate. There are number of standard search engines available today like Google, Bing, Ask, Dogpile etc but none of them is ideal. Every search services have different threshold ratios, different ranking algorithms leading to deviation in the output of each search result. Multi search services engaging different search engines can be solution to this problem. This paper presents Terrorist Meta Crawler, a web application that uses multiple search services to respond terrorist related user searches. Terrorist Meta Crawler sends web crawlers on different search engines to search terrorist information on web. Terrorist Network Mining can employ Terrorist Meta Crawler to mine vast ocean of data on web of the information of terrorist networks. This paper studies the Control Flow of Terrorist Meta Crawler for Terrorist Networking Mining application.

Over the past few decades there have been frequent terrorist attacks around the world including India. This article describes Terrorist Network Mining and problems faced during studying such networks. A major challenge faced by the law enforcement agencies is the large crime "raw" data volumes and the lack of sophisticated network analysis tools and techniques to utilize the data effectively and efficiently. This article states different data collection techniques used for terrorist networks. The major challenge is the development of the optimal noise reduction algorithm which will help in creating accurate linkage map of terrorist network without the loss of any key player node. This article successfully lists the factors that can be taken under consideration during generation of optimal noise reduction algorithm for Terrorist Web Mining. Once the accurate linkage map is generated the identification and removal of the key player for the destabilization of terrorist networks will become lot easier.