Computer Science ›› 2018, Vol. 45 ›› Issue (5): 123-130.doi: 10.11896/j.issn.1002-137X.2018.05.021

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Study on Secure Retrieval Scheme over Encrypted Data Supporting Result Ranking

YAO Han-bing, XING Na-na, ZHOU Jun-wei and LI Yong-hua   

  • Online:2018-05-15 Published:2018-07-25

Abstract: More and more organizations and users outsource their data into the low-cost and high-quality cloud storage.In order to protect the sensitive data,users will encrypt them before deployment,but this will bring big challenge to retrieval.This paper modified the traditional inverted index into the encrypted inverted index,and then built counting Bloom filter(CBF) on the encrypted inverted index.It proposed secure index based on counting Bloom filter(SICBF) to search encrypted data,which meet strict keyword and index privacy requirements.It also designed the CBF pruning algorithm to reduce redundancy of SICBF index.In order to protect the privacy of the relevance score(RSC) in SICBF,it employed one-to-many order-preserving mapping encryption(OPME) to encrypt RSC.The search results are directly sorted on the encrypted RSC,and only the most relevant top-k documents are returned to the authorized users.Security analysis illustrates that the encrypted RSC distribution is different from the original RSC,which hides the peak value of the RSC to prevent statistical attacks.The experiments show that the SICBF has high retrieval efficiency and low computational cost,which is suitable for searching massive encrypted data.

Key words: Inverted index,Relevance score,Counting bloom filter,Data privacy,Ranked search

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