Achieving Efficient Multi-Keyword Ranked Search over Encrypted Cloud Data Using Bloom Filters

<span title="2017-01-05">2017</span> <i title="International Journal of Science and Research"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/odv46yibm5gf7evzoopmrrqr3q" style="color: black;">International Journal of Science and Research (IJSR)</a> </i> &nbsp;
In emerging cloud computing, a central application is to outsource the files and record belonging to its user, to outer cloud servers for adaptable information storage. The outsourced documents and files should be encrypted because of the protection and secrecy worries of their proprietor. As there is large amount data present in the cloud it is very important to have a multi-keyword search over the encrypted data. Essentially huge amount of data is present on cloud and providing it for any
more &raquo; ... on demand request is difficult and is challenging. As searching is time consuming process it is important to provide multi keyword search giving a ranking result to get effective data. To maintain accuracy of search result and also provide better searching experience, it is important for such ranking system to provide multiple keyword searches, as single keyword search gives lots of noisy data. However, for privacy requirement encryption should be done on the sensitive data before outsourcing it, which obsoletes data utilization like information retrieval based on keyword. The main goal of efficient and secure search is building up the searchable encryption for multi-keyword ranked search over the scalable data documents that are stored on cloud.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21275/art20164430">doi:10.21275/art20164430</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/m2xykjs4dve7lb3fymkdpiz45i">fatcat:m2xykjs4dve7lb3fymkdpiz45i</a> </span>
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