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Privacy-Preserving Data Leakage Detection on Cloud

EasyChair Preprint no. 9938

13 pagesDate: April 6, 2023

Abstract

Digital files are compelled to hire local experts to take care of exposing the commercial public to their sophisticated data management systems cloud with the introduction of cloud computing for considerable flexibility and financial savings. However, before exporting, delicate information must be encoded in order to ensure data privacy, making plaintext keyword search useless for typical data usage. Therefore, it is crucial to enable a secure cloud data search tool. It is required to authorise numerous phrases used in the browse mandates and results records in the given sheer number of data users and documents in the cloud, they are listed in in order of how relevant to these phrases they are. Related research about encryption techniques tends to concentrate on Logical or single-word searches keyword searches, with little emphasis on sorting the search results. In this research, we identify and address the difficult issue of ranked multi-keyword search with privacypreserving over encryption key in cloud computing for the first time. (PDP(Provable Data Leakage Protection)). In order to create a safe system for utilising cloud data, we construct a set of stringent privacy standards. In order to accurately reflect how relevant data documents are to the search query, we select the effective similarity measure of "coordinate matching" from a variety of multi-keyword semantics. Moreover, we employ "inner product similarity" to statistically assess such a similarity metric. We first put out a fundamental concept for PDP (Provable Data Leakage Prevention) based on safe inner product computation. We next provide two vastly enhanced PDP (Provable Data Leakage Protection) schemes to meet varied rigorous privacy criteria in two distinct threat scenarios. We further expand these two approaches to accommodate more search semantics in an effort to enhance the data search service's search functionality.

Keyphrases: Cloud Computing, Encryption, PDP(Provable Data Leakage Protection)

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:9938,
  author = {R Baskar and R Pratheepraj and R Ragavan},
  title = {Privacy-Preserving Data Leakage Detection on Cloud},
  howpublished = {EasyChair Preprint no. 9938},

  year = {EasyChair, 2023}}
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