摘要
针对当前大数据隐私保护机制的局限性,提出一种社交网络隐私风险的模糊评估方法,引导对大数据隐私提供主动保护。在基于文献研究和专家访谈的基础上,定性分析大数据环境下社交网络的隐私风险因素,运用Delphi法构建包含3个准则维度和13个指标维度的隐私风险评估指标体系,采用层次分析法(AHP)和熵值法计算对各级指标的综合权重。通过问卷调查收集数据,对某社交网络的隐私风险进行模糊评估。实证分析结果表明,该社交网络平台的隐私风险等级处于较低风险,"管理制度"、"第三方信息搜集"、"隐私非法交易"等风险因素处于高风险。综合来看,隐私风险的模糊评估方法具有较好的适用性,可以为提升大数据环境下的社交网络服务水平提供借鉴。
According to the limitation of big data privacy protection, this paper proposed a fuzzy evaluation method of privacy risk for social network. The method can provide initiative protection for big data privacy. Based on literature reviews and experts interviews, the privacy risk factors of social network in big data environment are analyzed in qualitative. The paper designed the risk evaluation index system which consisted of three primary factors and thirteen secondary factors based on Delphi. Then, we used Analytic Hierarchy Process（AHP） and entropy method to determine the comprehensive weights of these factors. At last, the study of fuzzy evaluation of privacy risk for social network was conducted through questionnaires. The empirical analysis results show that the privacy risk level of social network platform is low, and the factors such as ＂management system＂, ＂third party information gathering＂, ＂privacy illegal trade＂ are in high risk. In conclusion, the meth- od could effectively evaluate privacy risk of social network, and it also provides advice to the social network service provid- ers so that they can improve the service quality in big data environment.
出处
《情报科学》
CSSCI
北大核心
2016年第9期94-98,共5页
Information Science
基金
国家自然科学基金项目(71503133)
国家社会科学基金特别委托项目(15&ZH012)
江苏高校品牌专业建设工程资助项目
关键词
大数据
社交网络
隐私风险
模糊评估
big data
social network
privacy risk
fuzzy evaluation
