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Enhancing Participatory Security Culture in Public Institutions: An Analysis of Organizational Employees' Security Threat Recognition Processesoa mark
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Publication Year
2024-01-01
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE Access, Vol.12, pp.47543-47558
Keyword
Malware threatsecurity policy compliance behaviortrust-risk modelTTATvignette experiment
Mesh Keyword
Malware threatMalwaresPolicy complianceRisk modelingSecuritySecurity policySecurity policy compliance behaviorTechnology threat avoidance theoryThreat-avoidance theoryTrust–risk modelVignette experiment
All Science Classification Codes (ASJC)
Computer Science (all)Materials Science (all)Engineering (all)
Abstract
This study recognizes the importance of employees' behavior in influencing the effectiveness of security alternatives despite the technical factors being well-established. As such, the study proposes a novel approach to reinforce security among employees, beginning with a practical case pertaining to their security compliance behavior. Utilizing the technology threat avoidance theory (TTAT) and the trust-risk model, the study explains the process by which employees voluntarily comply with information security policies upon perceiving a malware threat. It seeks to achieve this goal by employing a vignette experiment investigating how employees manage IT threats and conducting an empirical analysis of the factors impacting their compliance behavior with security policies in the context of malware threats. The findings indicate that raising employees' awareness of effective protective measures is critical in preventing or controlling malware while recognizing an appropriate threat level can enhance the persuasiveness of risk. By validating the proposed framework, this study could enable organizations to identify effective information security measures, thereby enhancing security culture reinforcement strategies to support sustainable growth. Future studies in different organizations could potentially increase the validity and generalizability of the findings.
ISSN
2169-3536
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/34070
DOI
https://doi.org/10.1109/access.2024.3383311
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Article
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Kang, Ju Young Image
Kang, Ju Young강주영
Department of Business Intelligence
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