Title :
Discovering criminal networks by Web structure mining
Author :
Hosseinkhani, Javad ; Chuprat, Suriayati ; Taherdoost, Hamed
Author_Institution :
Adv. Inf. Sch. (AIS), Univ. Teknol. Malaysia, Kuala Lumpur, Malaysia
Abstract :
Constantly, criminal web data create new and appropriate information for Law implementation. In scientific analysis, the digital data comprises of some information of social networks suspicious. On the other hand, consider in the evaluation of these pieces of information, this issue is challenging issue. In fact, a detective has to pull out the useful information from the text in web pages manually. Then, also create a link between different pieces of information and classify them into an organized database. Additionally, the organized database is ready to utilize several criminal network assessment tools for evaluation. However, the process of manually organizing data for evaluation is not effective for the reason that it is likely to have many errors. Moreover, its reliability is not persistent because the quality of resulted assessed data depends on the practice and experience of the agent. Therefore, the more professional is an operator, the better objectives will be achieved. The aim of this study is to propose a framework which shows the process of exploring of the criminal suspects of scientific data assessments based on orders capable pages and links that are covering the reliability gap.
Keywords :
Internet; data mining; database management systems; law; social networking (online); Web pages; Web structure mining; criminal Web data; criminal network assessment tools; criminal network discovery; criminal suspects; database; law implementation; scientific analysis; scientific data assessments; social networks; Crime Web Mining; Criminal Network; Forensics Analysis; Framework; Preferential Crawler; Social Network; Terrorist Network;
Conference_Titel :
Computing and Convergence Technology (ICCCT), 2012 7th International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-0894-6