부산대학교 도서관

Based on the rapid development of edge computing and resource-constrained characteristics, new requirements for edge information system security evaluation are proposed. Oriented to the resource-constrained scenarios of edge information systems and the distribution characteristics of raw data for security evaluation, the adaptability of existing models is improved. The improved principal component analysis (PCA-S method) based on Spearman’s coefficient is proposed for index screening. In order to further improve the screening effect and reduce the resource consumption of the security evaluation model, the PCA-S method and the Distinction degree screening method are combined by taking the intersection, and the PCA-SDC combination screening method is proposed. Through the PCA-SDC index combination screening, the coefficient of variation weighting, and the fuzzy comprehensive evaluation, the PSDC-CVF edge information system security evaluation model is finally formed. In order to assess the effect of index screening and security evaluation, three indicators, namely, the improved average quantity of information change degree, the average information contribution change degree, and the fuzzy evaluation deviation degree, are proposed. Through experiments, the improved PCA-S method and the combination screening PCA-SDC method are sequentially proved to be well adapted and effective in the index screening process of edge information system security evaluation. It is also verified that the PSDC-CVF model reduces the resource consumption compared with the traditional model and better balances the model energy consumption and performance.