标题：Data Combination Privacy Preservation Adjusting Mechanism for Software as a Service
作者：Zhang Kun; Abraham, Ajith; Shi Yuliang
作者机构：[Zhang Kun] Univ Jinan, Shandong Prov Key Lab Network Based Intelligent C, Jinan, Peoples R China.; [Abraham, Ajith] Univ Ostrava, VSB Tech, IT4Inno 更多
会议名称：IEEE International Conference on Systems, Man, and Cybernetics (SMC)
会议日期：OCT 13-16, 2013
来源：2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013)
关键词：cloud computing; data privacy; multi-tenancy; data combination privacy;; software as a service
摘要：In Software as a Service model, i.e. SaaS, tenants' sensitive data are stored and processed at the platform of un-trusted service providers. Data privacy has become the biggest challenge hindering wider adoption of software as a service. Data combination privacy has been proposed to protect privacy of data combination through sensitive association hidden. However, this approach doesn't consider the scenario where tenants' requirements changed and customization happened. When tenants customize data schema or privacy requirements, there is a possibility that underlying physical data chunk schema collides with the privacy requirements of tenants. This paper proposed the data combination privacy preservation adjusting mechanism for data privacy leakage caused by on demand customization of software as a service. Three principles of privacy preservation adjusting mechanism are proposed. Based on the adjusting mechanism, there would no more privacy leakage than before customization during the adjusting process to the customized schema. Analysis and experiments demonstrate the corrective and effective of the data privacy preservation adjusting mechanism for software as a service.