Cybercrime Profiling: Decision-Tree Induction, Examining Perceptions of Internet Risk and Cybercrime Victimisation
Al-Nemrat, A. and Benzaid, Chafika 2015. Cybercrime Profiling: Decision-Tree Induction, Examining Perceptions of Internet Risk and Cybercrime Victimisation. in: 2015 IEEE Trustcom/BigDataSE/ISPA IEEE. pp. 1380-1385
|Authors||Al-Nemrat, A. and Benzaid, Chafika|
The Internet can be a double-edged sword. While offering a range of benefits, it also provides an opportunity for criminals to extend their work to areas previously unimagined. Every country faces the same challenges regarding the fight against cybercrime and how to effectively promote security for its citizens and organisations. The main aim of this study is to introduce and apply a data-mining technique (decision-tree) to cybercrime profiling. This paper also aims to draw attention to the growing number of cybercrime victims, and the relationship between online behaviour and computer victimisation. This study used secondhand data collected for a study was carried out using Jordan a s a case study to investigate whether or not individuals effectively protect themselves against cybercrime, and to examine how perception of law influences actions towards incidents of cybercrime. In Jordan, cybercafe's have become culturally acceptable alternatives for individuals wishing to access the Internet in private, away from the prying eyes of society.
|Keywords||Classification tree; Digital forensics; Cybercrime profiling; Data mining|
|Book title||2015 IEEE Trustcom/BigDataSE/ISPA|
|03 Dec 2015|
|Publication process dates|
|Deposited||27 Feb 2017|
|Event||14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom-15)|
|Digital Object Identifier (DOI)||doi:10.1109/Trustcom.2015.534|
|Web address (URL)||http://doi.org/10.1109/Trustcom.2015.534|
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|Accepted author manuscript|
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