Acta Informatica Pragensia Vol. 7 No. 2

A Users’ Awareness Study and Influence of Socio-Demography Perception of Anti-Phishing Security Tips

DOI: https://doi.org/10.18267/j.aip.119

[plný text (PDF)]

Abdul Orunsolu, Omorinola Afolabi, Simon Sodiya, Adio Akinwale

N/A

Reference:
Alsharnouby, M., Alaca, F., & Chiasson, S. (2015). Why phishing still works: User strategies for combating phishing attacks. International Journal of Human-Computer Studies, 82, 70-82. doi: 10.1016/j.ijhcs.2015.05.005

APWG. (2017). APWG Phishing Attack Trends Reports. Anti-Phishing Working Group. Retrieved August 27, 2018, from: https://www.antiphishing.org/resources/apwg-reports/

Arachchilage N., & Love S. (2013). A game design framework for avoiding phishing attacks. Computers in Human Behavior, 29(3), 706-714. doi: 10.1016/j.chb.2012.12.018

Dhamija, R., Tygar, J.D. & Hearst, M. (2006). Why phishing works. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 581-590). New York: ACM. doi: 10.1145/1124772.1124861

Downs, J.S., Holbrook, M.B. & Cranor, L.F. (2006). Decision strategies and susceptibility to phishing. In Proceedings of the second symposium on Usable privacy and security (pp. 79-90). New York: ACM. doi: 10.1145/1143120.1143131

Hong, J. (2012). The state of phishing attacks. Communication of the ACM, 55(1), 74-81. doi: 10.1145/2063176.2063197

Jagatic, T., Johnson, N., Jakobsson, M. & Menczer, F. (2007). Social Phishing. Communications of the ACM, 50(10), 94-100. doi: 10.1145/1290958.1290968

Jakobsson, M. & Myers, S. A. (2007). Phishing and Countermeasures: Understanding the increasing problem of identity theft. New York: John Wiley & Sons.

Konradt, C., Schilling, A., & Werners, B. (2016). Phishing: An economic analysis of cybercrime perpetrators. Computers & Security, 58, 39-46. doi: 10.1016/j.cose.2015.12.001

Kumaraguru, P., Rhee, Y.W., Acquisti, A., Cranor, L., Hong, J., & Nunge, E. (2007). Protecting People from Phishing: The Design and Evaluation of an Embedded Training Email System. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 905-914). New York: ACM. doi: 10.1145/1240624.1240760

Li, Y., Yang, L. & Ding, J. (2016). A minimum enclosing ball-based support vector machine approach for detection of phishing websites. Optik - International Journal for Light and Electron Optics, 127(1), 345-351. doi: 10.1016/j.ijleo.2015.10.078

Lin, J., & Lu T. (2000). Towards an understanding of the behavioral intention to use a website. International Journal of Information Management, 20(3), 197-208. doi: 10.1016/S0268-4012(00)00005-0

Longe, T. (2014). Ensuring Information Security Assurance through Policy Framework. In Proceedings of the First National Cyber Security Forum. Nigeria: Punch News.

Maurer, M., & Hofer, L. (2012). Sophisticated Phishers Make More Spelling Mistakes: Using URL Similarity Against Phishing. In Cyberspace Safety and Security (pp. 414-426). Berlin: Springer. doi: 10.1007/978-3-642-35362-8_31

Neupane, A., Rahman, L., Saxena, N., & Hirshfield, L. (2015). A Multi-Modal Neuro-Physiological Study of Phishing Detection and Malware Warning. In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (pp. 479-491). New York: ACM. doi: 10.1145/2810103.2813660

Orunsolu, A.A, Alaran, M.A, Bamgboye, O.O, Sodiya, A.S., & Omorinola, A.O. (2016). A User’s Awareness Study of Anti-Phishing Security Tips. In Proceedings of the 2nd International Conference on Intelligent Computing and Emerging Technologies (pp. 46-55). Ilisan-Remo: Babcock University.

PandaLabs Report. (2012). PandaLabs Annual Report – 2012. Retrieved September 30, 2018, from: https://www.pandasecurity.com/mediacenter/social-media/pandalabs-annual-report-2012/

Parsons, K., McCormac, A., Pattinson, M., Butavicius, M., & Jerram, C. (2015). The design of phishing studies: Challenges for researchers. Computers & Security, 52, 194-206. doi: 10.1016/j.cose.2015.02.008

Ramanathan V., & Wechsler H. (2013). Phishing detection and impersonated entity discovery using Conditional Random Field and Latent Dirichlet Allocation. Computers & Security, 34, 123-139. doi: 10.1016/j.cose.2012.12.002

Sheng, S., Holbrook, M., Kumaraguru, P., Cranor, L.F. & Downs, J. (2010). Who falls for phish?: A demographic analysis of phishing susceptibility and the effectiveness of interventions. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 373-382). New York: ACM. doi: 10.1145/1753326.1753383

Vishwanath, A. (2016). Mobile device affordance: Explicating how smartphones influence the outcome of phishing attacks. Computers in Human Behavior, 63, 198-207. doi: 10.1016/j.chb.2016.05.035

Weby Vysoké školy ekonomické v Praze využívají pro optimalizaci svého obsahu a poskytovaných služeb cookies. Prosíme o udělení souhlasu s jejich uložením.

Vyberte služby, pro které chcete povolit využívání cookies: