PROJECT TITLE :

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

ABSTRACT:

With the arrival of cloud computing, it's become increasingly fashionable for information homeowners to outsource their knowledge to public cloud servers whereas allowing knowledge users to retrieve this information. For privacy concerns, secure searches over encrypted cloud data has motivated many research works underneath the only owner model. However, most cloud servers in follow don't simply serve one owner; instead, they support multiple house owners to share the benefits brought by cloud computing. During this paper, we propose schemes to deal with privacy preserving ranked multi-keyword search in an exceedingly multi-owner model (PRMSM). To enable cloud servers to perform secure search while not knowing the actual information of both keywords and trapdoors, we have a tendency to systematically construct a novel 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 function family. To stop 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 brand new information user authentication protocol. Furthermore, PRMSM supports efficient knowledge user revocation. Intensive experiments on real-world datasets confirm the efficacy and potency of PRMSM.