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高准确度网络安全意识个体评估及群体指数构建方法 被引量:6

A High Accuracy Method for Individual Assessment and Group Index Construction of Cyber Security Awareness
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摘要 针对网络安全意识评估方法存在评估准确度不及、客观性不足、缺少对群体的网络安全意识评估方法等问题,提出了一种高准确度的网络安全意识个体量化评估和群体指数构建方法.该方法从多个维度采集个体的网络安全意识数据,利用混合回归模型将安全数据量化为安全得分;利用改进的标签传播算法进行聚类,通过设定监督信息而不依赖标签数据,得到个体的信息安全意识等级;利用多个个体的信息安全意识评估结果,使用基于Grubbs准则构建的指数计算公式,弱化群体中的异常点,量化群体内部共同意识,得到群体网络安全意识指数.实验结果表明,相对现有的评估方法,该方法的准确度和客观性显著提升,同时能够正确反映群体网络安全意识水平,为网络安全意识的全面提升和闭环促进提供了技术方法. To achieve better results in the individual assessment and the group index construction of the cyber security awareness,a high-accurate method was proposed,combining with a set of different techniques.On the first stage,multi-dimension data acquisition and mixture of regression were introduced for the quantification of the security score.And then,gathering the extracted data with the improved label propagation algorithm,the awareness level was obtained based on the customized supervising data,being independent of tagged data.Furthermore,by using the Grubbs criterion to design the calculation function for group security index,to diminish the abnormal points and abstract the common features,the group index was constructed based on the evaluation results of cyber security awareness.Compared with the selected state-of-the-art counterparts,the proposed design can achieve a better accuracy and objectivity,and be able to demonstrate the general standard for the group security index.The results provide a effective method for the further study of the cyber security awareness.
作者 李蕊 潘丽敏 郝靖伟 张寒青 罗森林 吴倩 LI Rui;PAN Li-min;HAO Jing-wei;ZHANG Han-qing;LUO Sen-lin;WU Qian(School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China)
出处 《北京理工大学学报》 EI CAS CSCD 北大核心 2020年第9期1002-1008,共7页 Transactions of Beijing Institute of Technology
基金 国家“二四二”信息安全计划项目(2017A149)。
关键词 网络安全意识评估 混合回归模型 标签传播算法 Grubbs准则 cyber security awareness mix of regression label propagation algorithms Grubbs criterion
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