Privacy Preserving Ranked Multi-Keyword Search for Multiple Data Owners in Cloud Computing - 2016

PROJECT TITLE:

Privacy Preserving Ranked Multi-Keyword Search for Multiple Data Owners in Cloud Computing - 2016

ABSTRACT:

With the advent of Cloud Computing, it's become increasingly standard for data homeowners to outsource their data to public cloud servers whereas allowing knowledge users to retrieve this data. For privacy issues, secure searches over encrypted cloud information has motivated several research works beneath the only owner model. However, most cloud servers in practice don't just serve one owner; instead, they support multiple homeowners to share the advantages brought by Cloud Computing. In this paper, we tend to propose schemes to house privacy preserving ranked multi-keyword search in a multi-owner model (PRMSM). To enable cloud servers to perform secure search while not knowing the actual knowledge of both keywords and trapdoors, we tend to systematically construct a completely unique secure search protocol. To rank the search results and preserve the privacy of relevance scores between keywords and files, we have a tendency to propose a novel additive order and privacy preserving operate family. To prevent the attackers from eavesdropping secret keys and pretending to be legal knowledge users submitting searches, we propose a unique dynamic secret key generation protocol and a replacement knowledge user authentication protocol. Furthermore, PRMSM supports economical knowledge user revocation. Intensive experiments on real-world datasets ensure the efficacy and potency of PRMSM.

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