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A Parallel Multi-Keyword Top-k Search Scheme over Encrypted Cloud Data

EasyChair Preprint no. 1365

12 pagesDate: August 3, 2019


With searchable encryptions in the cloud computing, users can outsource their sensitive data in ciphertext to the cloud that provides efficient and privacy-preserving multi-keyword top-k searches. However, most existing top-k search schemes over encrypted cloud data are the centralize schemes which are limited in large scale data environment. To support scalable searches, we propose a parallel multi-keyword top-k search scheme over encrypted cloud data. In this scheme, the fragment-based encrypted inverted index is designed, which is indistinguishable and can be used for parallel searching. On the basis of such indexes, a Map-Reduce-based distributed computing framework is adopted to propose parallel multi-keyword top-k search algorithms. Security analysis and experiment evaluation show that the proposed scheme is privacy-preserving, efficient and scalable.

Keyphrases: Cloud Computing, distributed computing framework, document set, encrypted cloud data, fragment based encrypted inverted index, inverted index, keyword ranked search, keyword search, Map Reduce, Multi-keyword, Multi-keywords top-k Search, parallel computing, Posting list, privacy preserving, searchable encryption, TF-IDF Model, top-k search

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Maohu Yang and Hua Dai and Jingjing Bao and Xun Yi and Geng Yang},
  title = {A Parallel Multi-Keyword Top-k Search Scheme over Encrypted Cloud Data},
  howpublished = {EasyChair Preprint no. 1365},

  year = {EasyChair, 2019}}
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