Exploring The Correlation between Cyber Security Awareness, Protection Measures and the State of Victimhood: The Case Study of Ambo University’s Academic Staffs
DOI:
https://doi.org/10.13052/jcsm2245-1439.1044Keywords:
Cybersecurity awareness, multiple linear regression, protection measures, victimhood to cyber-crimeAbstract
The advancement of information communication technology has triggered a revolution in using the Internet for legitimate educational purposes on university campuses. Therefore, the Internet has changed the way of human communication and contributed to the development of mankind. On the other hand it is regrettable that its revolution has helped malicious users to exploit it for the malign purpose to commit a cyberspace crime that has in turn negatively affected fellow users who were preyed on by cyber predators. This work aimed to examine the awareness of cybersecurity, the measures taken to protect against cyberattacks and the state of victimization among professors at Ambo University. Thus, the present study comes up with the following findings. First, the result shows that the respondents’ cybersecurity awareness was significantly influenced by cyber-crime victimization, fields of study, and protection measures. Second, the current study also depicts that the respondents’ protection measures were connected to and influenced by cyber-crime victimization, education level, and cyber-security awareness. Finally, the study’s findings show that being a cyber-crime victim has been linked to predictors’ variables: protection measures and the level of cybersecurity awareness.
Downloads
References
M. Lagazio, N. Sherif, and M. Cushman, “A multi-level approach to understanding the impact of cyber crime on the financial sector,” Comput. Secur., vol. 45, pp. 58–74, 2014, doi: 10.1016/j.cose.2014.05.006.
N. Tosun and M. F. Baris, “The place and importance of computer and internetis in secondary school students’ life,” Procedia - Soc. Behav. Sci., vol. 28, pp. 530–535, 2011, doi: 10.1016/j.sbspro.2011.11.102.
M. Xin, J. Xing, W. Pengfei, L. Houru, W. Mengcheng, and Z. Hong, “Online activities, prevalence of Internet addiction and risk factors related to family and school among adolescents in China,” Addict. Behav. Reports, vol. 7, no. June 2017, pp. 14–18, 2018, doi: 10.1016/j.abrep.2017.10.003.
A. Bendovschi, “Cyber-Attacks – Trends, Patterns and Security Countermeasures,” Procedia Economics and Finance, vol. 28. pp. 24–31, 2015, doi: 10.1016/s2212-5671(15)01077-1.
M. Gercke, “Cybercrime Understanding Cybercrime :,” Underst. cybercrime phenomena, challenges Leg. response, no. ITU, p. 366, 2012, doi: 10.1088/1367-2630/11/1/013005.
M. H. Tibi, K. Hadeje, and B. Watted, “CybercrimeAwareness among Students at a Teacher Training College,” Int. J. Comput. Trends Technol., vol. 67, no. 6, pp. 11–17, 2019, doi: 10.14445/22312803/ijctt-v67i6p102.
European Economic and Social Committee, Cybersecurity : Ensuring awareness and resilience of the private sector across Europe in face of mounting cyber risks. 2018.
N. Kshetri, “Cybercrime and Cybersecurity in Africa,” J. Glob. Inf. Technol. Manag., vol. 22, no. 2, pp. 77–81, 2019, doi: 10.1080/1097198X.2019.1603527.
E. Kritzinger and B. Von Solms, “A framework for cyber security in Africa,” Innov. Vis. 2020 Sustain. growth, Entrep. Econ. Dev. - Proc. 19th Int. Bus. Inf. Manag. Assoc. Conf., vol. 1, pp. 438–447, 2012, doi: 10.5171/2012.322399.
D. Gefen, D. Straub, and M.-C. Boudreau, “Structural Equation Modeling and Regression: Guidelines for Research Practice,” Commun. Assoc. Inf. Syst., vol. 4, no. October, 2000, doi: 10.17705/1cais.00407.
X. Li and J. Li, “Statistical Human Genetics,” vol. 850, no. November 2014, pp. 411–421, 2012, doi: 10.1007/978-1-61779-555-8.
J. Jeon, “The strengths and limitations of the statistical modeling of complex social phenomenon: Focusing on SEM, path analysis, or multiple regression models,” Int. J. Soc. Behav. Educ. Econ. Bus. Ind. Eng., vol. 9, no. 5, pp. 1604–1612, 2015.
A. Alavifar, M. Karimimalayer, and M. K. Anuar, “Structural equation modeling VS multiple regression,” Eng. Sci. Technol. An Int. J., vol. 2, no. 2, pp. 326–329, 2012, [Online]. Available: http://www.estij.org/papers/vol2no22012/25vol2no2.pdf.
M. Mohd Ali, “Determinants of Preventing Cyber Crime: a Survey Research,” Int. J. Manag. Sci. Bus. Adm., vol. 2, no. 7, pp. 16–24, 2015, doi: 10.18775/ijmsba.1849-5664-5419.2014.27.1002.
P. Date, “UC Irvine UC Irvine Electronic Theses and Dissertations UNIVERSITY ! OF ! CALIFORNIA , !,” pp. 1982–2004, 2015.
M. Zwilling et al., “University of Huddersfield Factors that shape cybercrime victimisation and use,” Comput. Human Behav., vol. 69, no. December, pp. 317–334, 2016, doi: 10.14445/22312803/ijctt-v67i6p102.
K. Edwards, “Examining the Security Awareness, Information Privacy, and the Security Behaviors of Home Computer Users,” ProQuest Diss. Theses, no. 947, p. 160, 2015, [Online]. Available: https://nsuworks.nova.edu/gscis_etd%0Ahttps://proxy.cecybrary.com/login?url=https://search.proquest.com/docview/1773308920?accountid=26967.
S. M. Virtanen, “Fear of Cybercrime in Europe: Examining the Effects of Victimization and Vulnerabilities,” Psychiatry, Psychol. Law, vol. 24, no. 3, pp. 323–338, 2017, doi: 10.1080/13218719.2017.1315785.
A. K. Mokha, “A Study on Awareness of Cyber Crime and Security,” Research Journal of Humanities and Social Sciences, vol. 8, no. 4. p. 459, 2017, doi: 10.5958/2321-5828.2017.00067.5.
