Coordinate Matching for Effective Capturing the Similarity Between Query Keywords and Outsourced Documents

• Published in: IET Chennai 3rd International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2012) pp. 401 - 407
• Main Authors: Karapakula, A, Puramchand, M, Rafi, G.M
• Format: Conference Proceeding
• Language: English
• Published: Stevenage, UK IET 2012; The Institution of Engineering & Technology
• Subjects: Cryptography; Data security; Document processing techniques; Information retrieval techniques; Internet software; coordinate matching; text analysis; data retrieval; Boolean keyword search; multikeyword semantics; local sites; commercial public cloud; query processing; secure cloud data utilization system; threat models; data providers; multikeyword query; complex data management systems; data documents; cloud computing; inner product similarity; plaintext keyword search; cryptography; privacy-preserving multikeyword ranked search; Boolean algebra; sensitive data encryption; multikeyword ranked search over encrypted cloud data; outsourced documents; cloud data search service encryption; MRSE scheme; similarity ranking; secure inner product computation; data privacy
• ISBN: 1849197970; 9781849197977
• DOI: 10.1049/cp.2012.2246

As per the latest trend of cloud computing, data providers are motivated to send 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 sending, 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, for the first time, we define and solve the challenging problem of privacy-preserving multikeyword 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. Among various multi-keyword semantics, we choose the efficient principle of "coordinate matching", i.e., as many matches as possible, to capture the similarity between search query and data documents, and further use "inner product similarity" to quantitatively formalize such principle for similarity measurement. We first propose a basic MRSE scheme using secure inner product computation, and then significantly improve it to meet different privacy requirements in two levels of threat models. Thorough analysis investigating privacy and efficiency guarantees of proposed schemes is given, and experiments on the real-world dataset further show proposed schemes indeed introduce low overhead on computation and communication.