A survey of big data and data mining techniques for crime prevention

Authors

  • Noor ASM Faculty of Ocean Engineering, Technology and Informatics Computer Science Department, University Malaysia Terengganu, Terengganu, 21300, Malaysia
  • Sanusi SS Faculty of Ocean Engineering, Technology and Informatics Computer Science Department, University Malaysia Terengganu, Terengganu, 21300, Malaysia
  • Rahim NHA Faculty of Ocean Engineering, Technology and Informatics Computer Science Department, University Malaysia Terengganu, Terengganu, 21300, Malaysia

Keywords:

Big Data, Crimes, Data Mining, Survey

Abstract

Crimes remain a serious challenge to many societies and nations across the globe, despite technological advancement. Efforts by security agencies must remain a step ahead of potential attacks in order to effectively prevent crimes from occurring. The police stations and other related criminal justice departments have several large databases that can be used to forecast or examine criminal activities. Data Mining, the method of uncovering sensitive information from big data, is now an effective tool for combating, curbing and preventing crimes of all sorts. The main aim of this paper is to provide a systematic survey of how Data Mining techniques are applicable in combating crimes. In this paper, we selected widely applicable data mining techniques that were commonly used for crime analysis and prevention in previous related studies. A summary table of many relevant crime- Data Mining applications is included that will serve as a reference for researchers. Each technique has its specific use. Data mining methods are quickly explained to the reader that includes Classification, Cluster analysis, Association rue mining, Entity extraction and Social network analysis amongst others.

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Published

2024-02-26

How to Cite

Noor, A. S. M., Sanusi, S. S., & Rahim, N. H. A. (2024). A survey of big data and data mining techniques for crime prevention. COMPUSOFT: An International Journal of Advanced Computer Technology, 9(11), 3927–3933. Retrieved from https://ijact.in/index.php/j/article/view/601

Issue

Section

Review Article

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