Cyber Romance Scam Victimization Analysis using Routine Activity Theory Versus Apriori Algorithm
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 12
Abstract
The advance new digital era nowadays has led to the increasing cases of cyber romance scam in Malaysia. These technologies have offered both opportunities and challenge, depending on the purpose of the user. To face this challenge, the key factors that influence the susceptibility to cyber romance scam need to be identified. Therefore, this study proposed cyber romance scam models using statistical method and Apriori techniques to explore the key factors of cyber romance scam victimization based on the real police report lodged by the victims. The relationship between demographic variables such as age, education level, marital status, monthly income and independent variables such as level of computer skills and the level of cyber-fraud awareness has been investigated. Then, the result of this study was compared with Routine Activity Theory (RAT). This study found that those between the ages of 25 and 45 years were likely to be the victims of cyber romance scams in Malaysia. The majority of the victims are educated and having a Diploma. In addition, this research shows that married people are more likely to be the victims of cyber romance scams. Study shows that non-income individuals are also vulnerable to being the victims because the study shows that 17 percent of respondents who are the victims are from this group. As expected, those who work and have monthly income between RM2001 and above are more likely to be targeted and become a victim of cyber romance scams. The study also shows that those who lack computer skills and less levels of cyber-fraud awareness are more likely to be victims of cyber romance scams.
Authors and Affiliations
Mohd Ezri Saad, Siti Norul Huda Sheikh Abdullah, Mohd Zamri Murah
Keywords
Related Articles
- EP ID EP429223
- DOI 10.14569/IJACSA.2018.091267
- Views 102
- Downloads 0
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