Verifiable Simhash Blurred Keyword Search Scheme is Enable on the Encrypted Cloud Data

Authors

  • Yan Han, Jingyu Wang

Abstract

In order to protect data privacy, data owners will outsource the ciphertext of sensitive data to cloud server, which makes the traditional plaintext search technology difficult to use. For the search of encrypted cloud data, the traditional keyword fuzzy search scheme can search relevant documents, but the search results are not satisfactory. When the user inputs correctly, the approximate search cannot be completed. When the user has spelling errors, the returned results contain a large number of unrelated keyword documents, which seriously wastes bandwidth resources. Aiming at the defects of keyword fuzzy search in encrypted cloud data, a new keyword fuzzy search scheme is proposed. By calculating the relevance score of keywords and ranking the documents according to the relevance score, Top-k (i.e., the K documents with the highest correlation) are returned to the search users, which reduces unnecessary bandwidth waste and users' search for effective documents Time consumption, provides more effective search results, and through the introduction of false trapdoor set, it increases the difficulty of cloud server to analyze document keywords, and increases the privacy protection of the system.

Published

2020-10-01

Issue

Section

Articles