Research on data integration privacy preservation mechanism for DaaS - Zhi-gang ZHOU; Hong-li ZHANG; Xiang-zhan YU; Pan-pan LI (Tongxin xuebao)
The emergence of cloud computing provides a broader platform for multiple data owners to make integrated data publishing and collaborative data mining. In data-as-a-service (DaaS) model, integrated data was deployed in a cer-tain cloud platform with an untrusted service provider ta privacy leakage has become the challenge hindering applica-tion and popularization of DaaS model. For protecting privacy in the data integration stage, a two-layer privacy pro-tection mechanism for DaaS-oriented application was given, which was independent ith the specific applications, parti-tioning data attributes into different parts. In addition, the corres ding fake data set was used to assure the balanced distribution of data in each part, which realized privacy protection of data integration. The experimental results indicate that the proposed strategy is feasible, simultaneously has the low computing overhead.