JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2018, Vol. 53 ›› Issue (1): 53-62.doi: 10.6040/j.issn.1671-9352.2.2017.136

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Evaluation method for network security level based on cloud model and Bayesian feedback

ZHU Dan1, XIE Xiao-yao1*, XU Yang1, XIA Meng-ting2   

  1. 1. Guizhou Normal University, Key Laboratory of Information and Computing Science of Guizhou Province, Guiyang 550001, Guizhou, China;
    2. Computer Science and Engineering School of JUST, Zhenjiang 212003, Jiangsu, China
  • Received:2017-08-28 Online:2018-01-20 Published:2018-01-19

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Abstract: In view of the limitations of the evaluation staff on the content of the evaluation index and the fuzziness of judgment and the limitation of the judgment interval in quantitative evaluation of network security evaluation in information system level protection. The researchers combine the cloud model with the Bayesian feedback algorithm and adopt the cloud model theory to deal with the fuzziness and randomness of the evaluation results. Because the traditional one-dimensional reverse cloud algorithm appears hyper entropy is imaginary, therefore, researchers use the uncertainty of the reverse cloud algorithm to avoid the occurrence of negative entropy. Through the construction of Bayesian feedback cloud model, which is constructed to test and correct the evaluation results given by experts or reviewers which makes the final evaluation results more objective and accurate. According to the expectation and entropy of the overall correction cloud of network security and the reasonable security grade judgment interval is given as the basis of the grade evaluation in the actual evaluation. Verified by an example, the evaluation method proposed that can effectively correct the difference between the evaluation results of the evaluation personnel, realize the reasonable judgment division and give the objective and accurate grade evaluation result.

Key words: Bayesian feedback, network security grade evaluation, cloud model, the fuzziness of judgment, reverse cloud algorithm

CLC Number: 

  • TP301
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