The advent of cloud computing, data owners are motivated to outsource their complex data management systems from local sites to commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data has to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in cloud, it is crucial for the search service to allow multi-keyword query and provide result similarity ranking to meet the effective data retrieval need. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely differentiate the search results. In this paper, I define and solve the challenging problem of Privacy-Preserving Multi-Keyword Ranked Search over Encrypted cloud data (MRSE), and establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality. It uses the multikeyword semantics known as “coordinate matching”, i.e., as many matches as possible, to capture the similarity between search query and data documents. I propose a basic MRSE scheme using ABS(Attribute Based Encryption System) for encryption, and then significantly improve it to meet different privacy requirements using two algorithms OABS1 (Optimized Attribute Based Encryption System1), OABS2 (Optimized Attribute Based Encryption System2).
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