Impact of Habit on Online Fraud Mitigation

Kevin Kurniawan, Bonnie Soeherman

Abstract


User habits and their use of online mediums can make a bit difference, since the cyberspace is full of opportunities, as well as risks. Carelessness, especially in terms of data storage, information, and financial practices can lead to irreparable damages. The present paper provides a comprehensive overview of how the digital space has changed and how criminals take advantage of the vulnerabilities of internet users. The first section outlines the risk behavior and habits of users that invite cybercriminals and increase the threat of intrusion and data leak. The next section is dedicated to the detailed analysis of habits that can help users in prevent the crimes and mitigate their consequences. A set of recommendations is also presented towards the end of the paper, which is intended to assist users in identifying dubious online activities and prevent them before the crime happens. The paper makes use of scholarly and journal articles to establish its arguments

Keywords


Habit; Risk Mitigation; Online fraud

Full Text:

PDF

References


Atkins, B., & Huang, W. (2013). A study of social engineering in online frauds. Open Journal of Social Sciences, 1(03), 23.

Button, M., Nicholls, C. M., Kerr, J., & Owen, R. (2014). Online frauds: Learning from victims why they fall for these scams. Australian & New Zealand journal of criminology, 47(3), 391-408.

Chen, C. S., Su, S. A., & Hung, Y. C. (2011). Protecting Computer Users from Online Frauds U.S. Patent No. 7,958,555. Washington, DC: U.S. Patent and Trademark Office.

Chen, H., Beaudoin, C. E., & Hong, T. (2017). Securing online privacy: An empirical test on Internet scam victimization, online privacy concerns, and privacy protection behaviors. Computers in Human Behavior, 70, 291-302.

Christin, N., Yanagihara, S. S., & Kamataki, K. (2010). Dissecting one click frauds. ACM conference on Computer and communications security (pp. 15-26).

Davinson, N., & Sillence, E. (2010). It won’t happen to me: Promoting secure behavior among internet users. Computers in Human Behavior, 26(6), 1739-1747.

Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions of Internet shopping. Journal of Business Research, 56(11), 867-875.

Frantsiyants, K. (2019). Online Shopping: The Influence of the Internet on the Transformation of Consumers’ Buying Habits and Experiences (Doctoral dissertation, Empire State College).

Gupta, P., & Mundra, A. (2015). Online in-auction fraud detection using online hybrid model. In International Conference on Computing, Communication & Automation (pp. 901-907). IEEE.

Harrison, B., Vishwanath, A., & Rao, R. (2016). A user-centered approach to phishing susceptibility: The role of a suspicious personality in protecting against phishing. In 2016 49th Hawaii International Conference on System Sciences (HICSS) (pp. 5628-5634). IEEE.

Huie, S. C., Maguire, L. C., Malo, J. A., Inskeep, T. K., King, D. C., & Shroyer, D. C. (2013). Phishing redirect for consumer education: fraud detection. U.S. Patent No. 8,608,487. Washington, DC: U.S. Patent and Trademark Office.

López, A. U., Mateo, F., Navío-Marco, J., Martínez-Martínez, J. M., Gómez-Sanchís, J., Vila-Francés, J., & Serrano-López, A. J. (2019). Analysis of computer user behavior, security incidents and fraud using Self-Organizing Maps. Computers & Security, 83, 38-51.

Mahdhi, M., & Hickey, S. (2020). Six grand and a Rolex: lure of riches sucked me into online fraud. Retrieved 7 October 2020, from https://www.theguardian.com/technology/2020/feb/29/how-teenage-money-mules-funnel-millions-from-online-fraud

Maimon, D., Becker, M., Patil, S., & Katz, J. (2017). Self-protective behaviors over public WiFi networks. In The {LASER} workshop: Learning from authoritative security experiment results ({LASER} 2017) (pp. 69-76).

Maurya, A. (2012). Running Lean: Iterate from Plan A to a Plan That Works, Science of Aging Knowledge Environment. doi: 10.1126/sageke.2002.20.nw68.

Milne, G. R., Rohm, A. J., & Bahl, S. (2004). Consumers’ protection of online privacy and identity. Journal of Consumer Affairs, 38(2), 217-232.

Ortlinghaus, A., Zielke, S., & Dobbelstein, T. (2019). The impact of risk perceptions on the attitude toward multi-channel technologies. The International Review of Retail, Distribution and Consumer Research, 29(3), 262-284.

Tsang, S., Koh, Y. S., Dobbie, G., & Alam, S. (2014). Detecting online auction shilling frauds using supervised learning. Expert systems with applications, 41(6), 3027-3040.

Varghese, T. E., Fisher, J. B., Harris, S. L., & Durai, D. B. (2011). U.S. Patent No. 7,908,645. Washington, DC: U.S. Patent and Trademark Office.

Watts, S. (2016). Secure authentication is the only solution for vulnerable public wifi. Computer Fraud & Security, 2016(1), 18-20.

Yazdanifard, R., WanYusoff, W. F., Behora, A. C., & Sade, A. B. (2011). Electronic banking fraud: The need to enhance security and customer trust in online banking. Advances in Information Sciences and Service Sciences, 3(10), 505-509.

Yu, C. H., & Lin, S. J. (2013). Fuzzy rule optimization for online auction frauds detection based on genetic algorithm. Electronic Commerce Research, 13(2), 169-182.




DOI: https://doi.org/10.17509/jrak.v9i3.32182

Refbacks

  • There are currently no refbacks.


Creative Commons License

Jurnal Riset Akuntansi dan Keuangan  is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

View My Stats