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Title: Towards Intelligent Crime Investigation
Authors: Chamikara, M.A.P.
Yapa, Y.P.R. D.
Kodituwa, S.R.
Nawarathna, R.D.
Keywords: Crime Analysis
Data Mining
Data Integration
Decision Support Systems
Intelligent Led Policing
Law Enforcement
Issue Date: 6-Apr-2016
Publisher: SLIIT
Series/Report no.: NCTM 2016;001
Abstract: The tendency of the grave crimes shows that the security agencies have to shoulder the burden of the criminals in larger numbers than the past because considerable number of criminals already have been confined in many prisons and some were released after the punishment while many criminals have not even been caught. This perpetual trend has made the process of maintaining, investigating crimes very tedious and manual crime recording and investigation system has resulted inefficient crime analysis. Therefore, the retrieval an analysis of crime data has become a huge burden for the crime investigators. This paper presents an efficient method of utilizing data mining techniques along with a robust data mining framework (SL-CIDSS: Sri Lanka Crime Investigation Decision Support System) for intelligent crime investigation. The solution consists of an affluent set of data mining tools such as social network analysis, offender profiling, entity extraction, association rule mining, modus operandi analysis, etc. which provides a systematic way of crime investigation utilizing a proper controlling mechanism of the grave crimes. Security of data is ensured with Apache Shiro security framework for sensitive information and resources being accessed by a VPN (Virtually Private Network) implemented by Sri Lanka Telecom (SLT). The data mining tools have been tested for validity and accuracy by testing their results against the knowledge provided by a domain expert from Sri Lanka police department.
ISSN: 1800 3591
Appears in Collections:NCTM - SLIIT 2016

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