Abstract
Traditional information security risk assessment models usually rely on expert analysis to obtain prior knowledge, which leads to a greater impact on the results of security risk assessment by subjective bias. To solve this problem, we added the entropy weight method to the traditional Bayesian network-based information security risk assessment model. Entropy weight method is used to compute the weight coefficients of each risk factor involved in a risk event. Compared with traditional evaluation models, weighting risk factors during risk evaluation can effectively reduce the impact of excessive reliance on expert information, that is, excessive subjective factors, and theoretically improve the accuracy of the evaluation results. Finally, an instance of the risk assessment approach on the model is analyzed, which demonstrates the rationality and feasibility of this method.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China under Grant 61472048. We also would like to thank the anonymous reviewers for their detailed review and valuable comments, which have enhanced the quality of this paper.
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Lv, X., Shi, N., Wei, J., Tian, Y., Li, J., Li, J. (2022). Information System Security Risk Assessment Based on Entropy Weight Method - Bayesian Network. In: Cao, C., Zhang, Y., Hong, Y., Wang, D. (eds) Frontiers in Cyber Security. FCS 2021. Communications in Computer and Information Science, vol 1558. Springer, Singapore. https://doi.org/10.1007/978-981-19-0523-0_10
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DOI: https://doi.org/10.1007/978-981-19-0523-0_10
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