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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

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Impact factor: 8.15

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Paper Title: Improvised Privacy-Preserving Multi-keyword Top-k Similarity Search Over Encrypted Data
Authors Name: Pooja Kuber Patil , Rupali A. Mangrule
Unique Id: IJSDR1804053
Published In: Volume 3 Issue 4, April-2018
Abstract: Cloud computing enables individuals and organizations to run large, scalable computing to support large data applications in the domain, such as healthcare and scientific research. As a result, data owners are involved in outsourcing their data on cloud servers for data availability. However, data sets such as client files and records in electronic documents often contain sensitive information, which raises concerns about personal information, if the document is published or shared with some unreliable third party in the cloud. The most widely used and practical technique for keeping personal information is encrypting data before outsourcing to a cloud server. This reduces the utility of data and enables traditional data analysis operators. Fetching documents on k using outdated keywords. In this article, we will investigate the top-k search queries for multiple keywords for large data encodings to protect privacy, and attempt to identify effective and secure solutions for this problem. Particularly for privacy concerns about query data, we've created a special tree-like index structure and designed a randomized search algorithm that makes even the same search query create routes. Different views on the index can also be maintained. Under the stronger privacy. For query performance improvement, we have proposed a multi-layered top-k search scheme based on the concept of a partition, which contains a cluster of indexes based on the tree created for all documents. Finally, we combine these methods together as a powerful and secure way of identifying similar top-k searches. Our experimental results in real-life data sets show that the guidelines we offer can be improved. The ability to protect privacy, scalability, and efficiency in query processing is greatly enhanced by modern methods.
Keywords: Cloud computing, privacy preserving, data encryption, multi-keyword top-k search, trapdoor, cosine similarity, lucene indexing
Cite Article: "Improvised Privacy-Preserving Multi-keyword Top-k Similarity Search Over Encrypted Data", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.3, Issue 4, page no.319 - 322, April-2018, Available :http://www.ijsdr.org/papers/IJSDR1804053.pdf
Downloads: 000338719
Publication Details: Published Paper ID: IJSDR1804053
Registration ID:180042
Published In: Volume 3 Issue 4, April-2018
DOI (Digital Object Identifier):
Page No: 319 - 322
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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