Privacy Preserving Keywords Query For Secure Open Data Initiative

With the maturity of data analysis technology,data is at the heart of business operations and applications.Cloud computing provides a convenient solution for largescale data storage and data computing.By outsourcing data and computing to cloud service providers,data owners provide users with centralized,efficient query and retrieval services,thereby reducing the high cost of storing data.However,considering data privacy,data owners do not outsource sensitive data to cloud service providers(e.g.,financial data and medical data)in plaintext.It is the problem of “Encrypted data outsourcing”(EDO).At present,the solution proposed by the researchers are almost always applicable to the case of outsourcing data by a single data owner.However,because the business value of data has become apparent,the need for data sharing has increased significantly.The “open data initiative” allows the organizations from different countries to share and integrate their data to produce value added information products and services.However,the trust relationship between any two organizations can hardly be established due to the data sensitivity and their specific responsibilities.In this paper,we propose a secure string pattern query processing framework,which is used to support the secure data sharing for multiple data owners.Our contributions are as follows:(1)We propose a secure string pattern matching query processing framework to protect data privacy.With this framework,we design an efficient and secure index called Secure String PAttern Search tree(S2PAStree),which allows the execution of the string pattern query in logarithmic time complexity.(2)Under the scenario that multiple data owners open their data with privacy concerns,we propose a secure index construction protocols,including secure cluster similarity calculation protocols and a secure Bloom filter merge protocol.We give detailed protocol security analyses,which prove that the protocol can achieve the goals of the data privacy,the data pattern privacy,and the index privacy.