Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Privacy Preserving Keyword Search by Index Confidentiality

Author : Sampada K S 1 N P Kavya 2

Date of Publication :17th March 2021

Abstract: Data owners are encouraged to outlet their data to the cloud for greater flexibility and suitability. Cloud storage is a third party server which always raises question of Privacy and confidentiality. Most of the cloud servers extend to provide confidentiality by encrypting the data before outsourcing. This demands verifiability of the encrypted files that are retrieved from the cloud by the users using Query keyword search. This paper focuses on study of various search techniques over encrypted data and the threat models posed by each one of them, and then enhances on building index confidentiality for Privacy Preserving Keyword Search (PPKS). An improved privacy preserving keyword search scheme over encrypted data is being proposed to address this problem. To enable users to search over encrypted data, we use the tree structure with m-levels to build search index. The index is encrypted using secret key which is generated using random numbers. The tree is split into levels based on these secret key factors. Thus the index vectors are encrypted. Query vectors are also encrypted in the same manner and the similarity measure is considered to find the relevant document. The documents which have the highest similarity measure are considered to be relevant. The proposed model in this paper addresses the issue on known cipher text attack.

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