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Risk Assessment of Insider Threats Based on IHFACS-BN

Author

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  • Min Zeng

    (School of Economics, Management and Law, University of South China, Hengyang 421001, China
    These authors contributed equally to this work.)

  • Chuanzhou Dian

    (School of Economics, Management and Law, University of South China, Hengyang 421001, China
    These authors contributed equally to this work.)

  • Yaoyao Wei

    (School of Economics, Management and Law, University of South China, Hengyang 421001, China)

Abstract

Insider threats, as one of the pressing challenges that threaten an organization’s information assets, usually result in considerable losses to the business. It is necessary to explore the key human factors that enterprise information security management should focus on preventing to reduce the probability of insider threats effectively. This paper first puts forward the improved Human Factors Analysis and Classification System (IHFACS) based on actual enterprise management. Then, the enterprise internal threat risk assessment model is constructed using the Bayesian network, expert evaluation, and fuzzy set theory. Forty-three classic insider threat cases from China, the United States, and Israel during 2009–2021 are selected as samples. Then, reasoning and sensitivity analysis recognizes the top 10 most critical human factors of the accident and the most likely causal chain of unsafe acts. The result shows that the most unsafe behavior was not assessing employees’ familiarity with the company’s internal security policies. In addition, improving the organizational impact of information security can effectively reduce internal threats and promote the sustainable development of enterprises.

Suggested Citation

  • Min Zeng & Chuanzhou Dian & Yaoyao Wei, 2022. "Risk Assessment of Insider Threats Based on IHFACS-BN," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:491-:d:1017415
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    References listed on IDEAS

    as
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    4. Cao, Cejun & Liu, Yang & Tang, Ou & Gao, Xuehong, 2021. "A fuzzy bi-level optimization model for multi-period post-disaster relief distribution in sustainable humanitarian supply chains," International Journal of Production Economics, Elsevier, vol. 235(C).
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