MOBILE SECURITY PRACTICES AMONG MALAYSIAN CITIZENS: A SURVEY OF RISK AWARENESS AND PROTECTIVE BEHAVIORS

QIN QIN; Nur Suhaili  Mansor; Hapini Awang; Huda Ibrahim; Adi Permana Sidik

doi:10.61397/tla.v3i2.512

Authors

QIN QIN Universiti Utara Malaysia
Nur Suhaili Mansor Universiti Utara Malaysia
Hapini Awang Universiti Utara Malaysia
Huda Ibrahim Universiti Utara Malaysia
Adi Permana Sidik Universitas Sangga Buana YPKP

DOI:

https://doi.org/10.61397/tla.v3i2.512

Keywords:

Cyber Threats, Malaysia, Gender Differences, Risk Awareness

Abstract

Mobile phones have become an important part of Malaysian youth's daily lives, and as easy as it is to get our hands on a mobile, the growing issues that follow raise alarms for cybersecurity. WordPress site. Although there has been a recent influx of online scam and privacy breach reports, little still exists on how ordinary users perceive mobile security, or if their behaviors are consistent with good risk mitigation practices. This study aims to examine the relationships that exist among mobile security confidence, user practices, and incident experiences with the gender of Malaysian youth. Using an eight-sectioned structured survey as an evaluation instrument, key findings are mainly gleaned from users who report medium levels of confidence in their mobile malware knowledge and overall adoption of protective behaviors such as keeping software updated, only using trusted sources to download apps, and using biometrics. A total of 38.1% of respondents, meanwhile, admitted to previous security incidents largely borne out of the presence of outdated systems and a lack of oversight elements in place for vetting third-party applications. in a rapidly digitizing society. Yet without habitual practice and supportive system design, awareness alone may not be enough.

References

Alsharida, R. A., Al-rimy, B. A. S., Al-Emran, M., & Zainal, A. (2023). A systematic review of multi perspectives on human cybersecurity behavior. Technology in Society, 73, 102258. https://doi.org/10.1016/j.techsoc.2023.102258

Bwalya, D., & Phiri, J. (2023). Fraud Detection in Mobile Banking Based on Artificial Intelligence. In R. Silhavy & P. Silhavy (Eds.), Artificial Intelligence Application in Networks and Systems (pp. 537–554). Springer International Publishing. https://doi.org/10.1007/978-3-031-35314-7_48

Daengsi, T., Pornpongtechavanich, P., & Wuttidittachotti, P. (2022). Cybersecurity Awareness Enhancement: A Study of the Effects of Age and Gender of Thai Employees Associated with Phishing Attacks. Education and Information Technologies, 27(4), 4729–4752. https://doi.org/10.1007/s10639-021-10806-7

Debb, S. M., & McClellan, M. K. (2021). Perceived Vulnerability As a Determinant of Increased Risk for Cybersecurity Risk Behavior. Cyberpsychology, Behavior, and Social Networking, 24(9), 605–611. https://doi.org/10.1089/cyber.2021.0043

Hong, Y., & Furnell, S. (2021). Understanding cybersecurity behavioral habits: Insights from situational support. Journal of Information Security and Applications, 57, 102710. https://doi.org/10.1016/j.jisa.2020.102710

Hopcan, S., Türkmen, G., & Polat, E. (2024). Exploring the artificial intelligence anxiety and machine learning attitudes of teacher candidates. Education and Information Technologies, 29(6), 7281–7301. https://doi.org/10.1007/s10639-023-12086-9

Keyes, K. M., & Platt, J. M. (2024). Annual Research Review: Sex, gender, and internalizing conditions among adolescents in the 21st century – trends, causes, consequences. Journal of Child Psychology and Psychiatry, 65(4), 384–407. https://doi.org/10.1111/jcpp.13864

Lebek, B., Uffen, J., Neumann, M., Hohler, B., & H. Breitner, M. (2014). Information security awareness and behavior: A theory-based literature review. Management Research Review, 37(12), 1049–1092. https://doi.org/10.1108/MRR-04-2013-0085

Luo, Y., Wang, G., Li, Y., & Ye, Q. (2021). Examining Protection Motivation and Network Externality Perspective Regarding the Continued Intention to Use M-Health Apps. International Journal of Environmental Research and Public Health, 18(11), Article 11. https://doi.org/10.3390/ijerph18115684

Morán-Soto, G., & González-Peña, O. I. (2022). Mathematics Anxiety and Self-Efficacy of Mexican Engineering Students: Is There Gender Gap? Education Sciences, 12(6), Article 6. https://doi.org/10.3390/educsci12060391

Ogden, S. E. (n.d.). CYBERSECURITY: CREATING A CYBERSECURITY CULTURE.

Patel, S., & Doshi, N. (2022). Internet of Behavior in Cybersecurity: Opportunities and Challenges. In P. K. Singh, S. T. Wierzchoń, J. K. Chhabra, & S. Tanwar (Eds.), Futuristic Trends in Networks and Computing Technologies (pp. 219–227). Springer Nature. https://doi.org/10.1007/978-981-19-5037-7_14

Sulaiman, N. S., Fauzi, M. A., Hussain, S., & Wider, W. (2022). Cybersecurity Behavior among Government Employees: The Role of Protection Motivation Theory and Responsibility in Mitigating Cyberattacks. Information, 13(9), Article 9. https://doi.org/10.3390/info13090413

Yadav, C. S., Singh, J., Yadav, A., Pattanayak, H. S., Kumar, R., Khan, A. A., Haq, M. A., Alhussen, A., & Alharby, S. (2022). Malware Analysis in IoT & Android Systems with Defensive Mechanism. Electronics, 11(15), Article 15. https://doi.org/10.3390/electronics11152354

Yanti, A., Yani, M., Saputra, I., Zaman, N., & Maulana, T. (2024). An Analysis of Determinants Affecting the Utilization of Integrated Non-Communicable Disease Service Posts (Posbindu PTM) in the Ulee Kareng Public Health Center, Banda Aceh City: A Health Belief Model Approach. Universal Publication Index E-Library, 101–127.

Zhou, K. Z., Cao, J., Yuan, X., Weissglass, D. E., Kilhoffer, Z., Sanfilippo, M. R., & Tong, X. (2023). “I’m Not Confident in Debiasing AI Systems Since I Know Too Little”: Teaching AI Creators About Gender Bias Through Hands-on Tutorials (No. arXiv:2309.08121). arXiv. https://doi.org/10.48550/arXiv.2309.08121

Zou, Y., Le, K., Mayer, P., Acquisti, A., Aviv, A. J., & Schaub, F. (2024). Encouraging Users to Change Breached Passwords Using the Protection Motivation Theory. ACM Transactions on Computer-Human Interaction, 31(5), 1–45. https://doi.org/10.1145/3689432