SaaS环境下的数据隐私保护机制研究

Research on data privacy protection mechanism in SaaS environment

在软件即服务(SaaS)环境下,由于租户数据统一保存在云中,因而具有隐私泄露的风险。综合考虑数据使用效率和数据隐私保护两个方面,提出一种租户数据隐私保护策略。首先,根据日志数据进行属性聚类,使得关联度较高的属性聚集到一起,以确保数据应用效率;然后,根据隐私约束条件对聚类后的每个属性集合做进一步的划分,生成可以避免数据隐私泄露的数据分割策略;最后,利用第三方的可信云实现数据隐私分割策略的保存,并依此进行租户数据表的分割和重构。对比实验结果表明,提出的数据隐私分割算法整体来说具有较好的性能,可以实现100%的隐私保护效果。

In Software as a Service(SaaS)environments,there is a risk of privacy leakage as tenant data is stored in the cloud. In comprehensive consideration of data use efficiency and data privacy protection,a strategy of tenant data privacy protection is proposed. The attribute clustering is carried out according to log data to get the high correlation attributes together to ensure the efficiency of data application. The each clustered attribute set is further divided according to the privacy constraints to generate a data segmentation strategy which can avoid data privacy leakage. The protection of the data privacy segmentation strategy is realized by means of the trusted cloud of third side. By relying on this,the data table of its tenant is split and reconstructed. The comparison experiment results show that the data privacy segmentation algorithm proposed in this paper has better performance on the whole,and can achieve 100% privacy protection effect.