Media Impact on Mobile Phishing Avoidance Behavior
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Source | Journal of Information Systems Security Volume 20, Number 3 (2024)
Pages 147–165
ISSN 1551-0123 (Print)ISSN 1551-0808 (Online) |
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Authors | Xiaoqing Li — The University of Illinois at Springfield, USA | ||
Publisher | Information Institute Publishing, Washington DC, USA |
Abstract
Mobile phishing avoidance is a crucial topic in cybersecurity research. In this study, we investigate the influence of various forms of media on individuals' motivation to prevent mobile phishing attacks. Based on the technology threat avoidance theory (TTAT), our study extends a current research model regarding mobile phishing avoidance by introducing media influence. We gathered 286 valid responses from Amazon Mechanical Turk (MTurk) participants. Our research findings indicate the significant role of news media in motivating users to avoid mobile phishing attacks. With this proposed framework, researchers and practitioners can purposely investigate how to incorporate news media to help users prevent mobile phishing.
Keywords
Mobile Phishing Avoidance, News Media Influence, Anticipated Regret, Antiphishing Self-efficacy.
References
Ajzen, I., Brown, T. C., and Carvajal, F. (2004). Explaining the Discrepancy between Intentions and Actions: The Case of Hypothetical Bias in Contingent Valuation. Personality and Social Psychology Bulletin, 30(9), 1108–1121.
Aleroud, A. and Zhou, L. (2017). Phishing Environments, Techniques, and Countermeasures: A Survey. Computers & Security, 68, 160–196.
AlGhanboosi, B., Ali, S., and Tarhini, A. (2023). Examining the effect of regulatory factors on avoiding online blackmail threats on social media: A structural equation modeling approach. Computers in Human Behavior, 144, 107702.
Arachchilage, N. A. G. and Love, S. (2014). Security awareness of computer users: A phishing threat avoidance perspective. Computers in Human Behavior, 38, 304-312.
Arachchilage, N. A. G., Love, S., and Beznosov, K. (2016). Phishing threat avoidance behaviour: An empirical investigation. Computers in Human Behavior, 60, 185–197.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215.
Brodin, M. and Rose, J. (2020). Improving Mobile Security Management in SME's: The MSME Framework. Journal of Information Systems Security, 16 (1), 47-75.
Bushman, B. J. and Whitaker, J. (2012). Media influence on behavior. In Encyclopedia of human behavior (2nd ed., pp. 571–575). Elsevier Inc.
Cialdini, R. B. (2009) Influence: Science and practice (5th ed.). Scott Foresman. https://www.researchgate.net/publication/
229067982_Influence_Science_and_Practice
Crossler, R. E., Johnston, A. C., Lowry, P. B., Hu, Q., Warkentin, M., and Baskerville, R. (2013). Future directions for behavioral information security research. Computers & Security, 32, 90–101.
Curtis, S. R., Rajivan, P., Jones, D. N., and Gonzale, C. (2018). Phishing attempts among the dark triad: Patterns of attack and vulnerability. Computers in Human Behavior, 87, 174–182.
De Fano, D., Schena, R., and Russo, A. (2022). Empowering plastic recycling: Empirical investigation on the influence of social media on consumer behavior. Resources, Conservation and Recycling, 182, 106269. ISSN 0921-3449.
Enikolopov, R. and Petrova, M. (2017). Mass media and its influence on behaviour (Vol. 44). Centre de Recerca en Economia Internacional (CREI).
Fornell, C. and Larcker, D. F. (1981). Evaluating structural equation models with unobserved variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Gallagher, K., Zhang, X., and Gallagher, V. C. (2019). Antecedents of Information Security Activities: Drivers, Enablers, and Constraints. Journal of Information Systems Security, 15 (1), 27-60.
Gerbner G, Gross L, Morgan M, et al. (1994). Growing up with television: The cultivation perspective. In: Bryant J and Zillmann D (eds) Media Effects: Advances in Theory and Research. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc., 17–41.
Ghose, S. M., Dzierzewski, J. M., and Dautovich, N. D. (2022). Sleep and self-efficacy: The role of domain specificity in predicting sleep health. Sleep Health, 9(2) 190–195.
Goel, D. and Jain, A. K. (2018). Mobile phishing attacks and defence mechanisms: State of art and open research challenges. Computers & Security, 73, 519–544.
Grover, P., Kar, A. K., and Dwivedi, Y. (2022). The evolution of social media influence - A literature review and research agenda. International Journal of Information Management Data Insights, 2(2), 100116.
Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd edition). Los Angeles: Sage.
Hassan, L. M., Shiu, E., and Shaw, D. (2016). Who says there is an intention–behaviour gap? Assessing the empirical evidence of an intention–behaviour gap in ethical consumption. Journal of Business Ethics, 136(2), 219–236.
Jagatic, T. N., Johnson, N. A., Jakobsson, M., and Menczer, F. (2017). Social phishing. Communications of the ACM, 50(10), 94–100.
Liang, H. and Xue, Y. (2009). Avoidance of information technology threats: A theoretical perspective. MIS Quarterly, 33(1), 71–90.
Liang, H. and Xue, Y. (2010). Understanding security behaviors in personal computer usage: A threat avoidance perspective. Journal of the Association for Information Systems, 11(7), 394–413.
Mathews, L. (2017). Phishing scams cost American businesses half a billion dollars a year. Forbes. https://www.forbes.com/sites/leemathews/2017/05/05/phishing-scams-cost-american-businesses-half-a-billion-dollars-a-year/?sh=71f8e843fa1c
Marett, K. and Nabors, M. (2021). Local learning from municipal ransomware attacks: A geographically weighted analysis. Information & Management, 58(103482).
Marotta, A. and Madnick, S. (2020). Perspectives on the Relationship between Compliance and Cybersecurity. Journal of Information Systems Security, 16(3), 151–177.
Mayer-Brown, S., Lawless, C., Fedele, D., Dumont-Driscoll, M., and Janicke, D. M. (2016). The effects of media, self-esteem, and BMI on youth's unhealthy weight control behaviors. Eating Behaviors, 21, 59–65.
Martens, M., De Wolf, R., and De Marez, L. (2019). Investigating and comparing the predictors of the intention towards taking security measures against malware, scams, and cybercrime in general. Computers in Human Behavior, 92, 139-150. ISSN 0747-5632.
Nekmahmud, M., Naz, F., Ramkissoon, H., and Fekete-Farkas, M. (2022). Transforming consumers' intention to purchase green products: Role of social media. Technological Forecasting and Social Change, 185, 122067.
Nunnally, J. (1978). Psychometric theory (2nd edition). New York: McGraw-Hill.
Pokharel, M., Lillie, H. M., Nagatsuka, K., Barbour, J. B., Ratcliff, C. L., and Jensen, J. D. (2023). Social media narratives can influence vaccine intentions: The impact of depicting regret and character death. Computers in Human Behavior, 141, 107612. ISSN 0747-5632.
Qabajeh, I., Thabtah, F., and Chiclana, F. (2018). A recent review of conventional vs. automated cybersecurity antiphishing techniques. Computer Science Review, 29, 44–55.
Shillair, R., Esteve-González, P., Dutton, W. H., Creese, S., Nagyfejeo, E., and von Solms, B. (2022). Cybersecurity education, awareness raising, and training initiatives: National level evidence-based results, challenges, and promise. Computers & Security, 119, 102756.
Sreedevi, A. G., Harshitha, T. N., Sugumaran, V., and Shanka, P. (2022). Application of cognitive computing in healthcare, cybersecurity, big data and IoT: A literature review. Information Processing & Management, 59(2), 102888.
Sultana, T., Dhillon, G., and Oliveira, T. (2023). The effect of fear and situational motivation on online information avoidance: The case of COVID-19. International Journal of Information Management, 69, 102596.
Sun, J. C. Y., Yu, S. J., Lin, S. S. J., and Tseng, S. S. (2016). The mediating effect of antiphishing self-efficacy between college students’ internet self-efficacy and antiphishing behavior and gender difference. Computers in Human Behavior, 59, 249-257.
Sutton, S. (1998). Predicting and explaining intentions and behavior: How well are we doing? Journal of Applied Social Psychology, 28, 1317–1338.
Syed, R. (2020). Cybersecurity vulnerability management: A conceptual ontology and cyber intelligence alert system. Information & Management, 57(6), 103334.
Tang, Z., Millera, A. S., Zhou, Z., and Warkentin, M. (2021). Does government social media promote users' information security behavior towards COVID-19 scams? Cultivation effects and protective motivations. Government Information Quarterly, 38(2), 101572.
Thompson, N., McGill, T. J., and Wang, X. (2017). “Security begins at home”: Determinants of home computer and mobile device security behavior. Computers & Security, 70, 376–391.
Torten, R., Reaiche, C., and Boyle, S. (2018). The impact of security awareness on information technology professionals’ behavior. Computers & Security, 79, 68–79.
Tsay-Vogel, M., Shanahan, J., and Signorielli, N. (2018). Social media cultivating perceptions of privacy: A 5-year analysis of privacy attitudes and self-disclosure behaviors among Facebook users. New Media & Society.
Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–487.
Verkijika, S. F. (2018). Understanding smartphone security behaviors: An extension of the protection motivation theory with anticipated regret. Computers & Security, 77, 860–870.
Verkijika, S. F. (2019). “If you know what to do, will you take action to avoid mobile phishing attacks”: Self-efficacy, anticipated regret, and gender. Computers in Human Behavior, 101, 286–296.
Vishwanath, A. (2016). Mobile device affordance: Explicating how smartphones influence the outcome of phishing attacks. Computers in Human Behavior, 63, 198–207.
Wright, R. T., Jensen, M. L., Thatcher, J. B., Dinger, M., and Marett, K. (2014). Research note—Influence techniques in phishing attacks: An examination of vulnerability and resistance. Information Systems Research, 25(2), 385–400.
Zeelenberg, M., and Pieters, R. (2007). A theory of regret regulation 1.0. Journal of Consumer Psychology, 17(1), 3–18.
Zhou, Y., Li, Y.-Q., Ruan, W.-Q., and Zhang, S.-N. (2023). Owned media or earned media? The influence of social media types on impulse buying intention in internet celebrity restaurants. International Journal of Hospitality Management, 111, 103487.