Secure K-NN Query on Encrypted Cloud Data with Multiple Keys

Author:

Vignesh R.,Deepa D.,Mana Suja Cherukullath,Keerthi Samhitha B.

Abstract

Abstract Cloud computing has become an undeniably famous assistance for its adaptability and versatility, which rouses numerous associations, foundations and organizations to want to re-appropriate data administrations to cloud stage. Simultaneously, much consideration has been paid to adapt to the extraordinary security and protection issues in recloud cloud. The general methodology is to scramble data by the data owner (DO) before re-appropriating; the approved query user play out an unpredictable arrangement of encryption and decoding tasks during question execution. In any case, the above plans have accepted that the question clients are completely trusted and have the entrance to the key for scrambling and unscrambling recloud data. It will achieve a few issues in reality. So we propose a novel plan for secure KNN inquiry on encoded cloud data with various keys, in which the data owner and each question client all hold their own various keys, and don’t impart them to one another; in the interim, the data owner scrambles and decodes re-appropriated data utilizing the key of his own. Our plan is built by set of conventions to jelly the data classification and question over scrambled cloud data without key-sharing.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference30 articles.

1. Secure knn computation on encrypted databases;Wong;in Proceedings of the 2009 ACM SIGMOD International Conference on Management of data.ACM,2009

2. Virtualized in-cloud security services for mobile devices;Oberheide;Proceedings of the First Workshop on Virtualization in Mobile Computing,2008

3. An Efficient Dynamic Indexing and Metadata BasedStorage in Cloud Environment;Anjanadevi

4. Enabling secure andefficient ranked keyword search over outsourced cloud data;Wang;Parallel and Cloud Systems, IEEE Transactions on,2012

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