Countering statistical attacks in cloud-based searchable encryption
Searchable encryption (SE) is appearing as a prominent solution in the intersection of privacy protection and efficient retrieval of data outsourced to cloud computing storage. While it preserves privacy by encrypting data, yet supports search operation without data leakage. Due to its applicability...
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my.um.eprints.366272024-08-13T07:44:55Z http://eprints.um.edu.my/36627/ Countering statistical attacks in cloud-based searchable encryption Ahsan, M. A. Manazir Ali, Ihsan Idris, Mohd Yamani Idna Imran, Muhammad Shoaib, Muhammad QA75 Electronic computers. Computer science Searchable encryption (SE) is appearing as a prominent solution in the intersection of privacy protection and efficient retrieval of data outsourced to cloud computing storage. While it preserves privacy by encrypting data, yet supports search operation without data leakage. Due to its applicability, many research communities have proposed different SE schemes under various security definitions with numerous customary features (i.e. multi keyword search, ranked search). However, by reason of multi-keyword ranked search, SE discloses encrypted document list corresponding to multiple (secure) query keywords (or trapdoor). Such disclosure of statistical information helps an attacker to analyze and deduce the content of the data. To counter statistical information leakage in SE, we propose a scheme referred to as Countering Statistical Attack in Cloud based Searchable Encryption (CSA-CSE) that resorts to randomness in all components of an SE. CSA-CSE adopts inverted index that is built with a hash digest of a pair of keywords. Unlike existing schemes, ranking factors (i.e. relevance scores) rank the documents and then they no longer exist in the secure index (neither in order preserving encrypted form). Query keywords are also garbled with randomness in order to hide actual query/result statistics. Our security analysis and experiment on request for comments database ensure the security and efficiency of CSA-CSE. Springer/Plenum Publishers 2020-06 Article PeerReviewed Ahsan, M. A. Manazir and Ali, Ihsan and Idris, Mohd Yamani Idna and Imran, Muhammad and Shoaib, Muhammad (2020) Countering statistical attacks in cloud-based searchable encryption. International Journal of Parallel Programming, 48 (3). pp. 470-495. |
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QA75 Electronic computers. Computer science Ahsan, M. A. Manazir Ali, Ihsan Idris, Mohd Yamani Idna Imran, Muhammad Shoaib, Muhammad Countering statistical attacks in cloud-based searchable encryption |
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Searchable encryption (SE) is appearing as a prominent solution in the intersection of privacy protection and efficient retrieval of data outsourced to cloud computing storage. While it preserves privacy by encrypting data, yet supports search operation without data leakage. Due to its applicability, many research communities have proposed different SE schemes under various security definitions with numerous customary features (i.e. multi keyword search, ranked search). However, by reason of multi-keyword ranked search, SE discloses encrypted document list corresponding to multiple (secure) query keywords (or trapdoor). Such disclosure of statistical information helps an attacker to analyze and deduce the content of the data. To counter statistical information leakage in SE, we propose a scheme referred to as Countering Statistical Attack in Cloud based Searchable Encryption (CSA-CSE) that resorts to randomness in all components of an SE. CSA-CSE adopts inverted index that is built with a hash digest of a pair of keywords. Unlike existing schemes, ranking factors (i.e. relevance scores) rank the documents and then they no longer exist in the secure index (neither in order preserving encrypted form). Query keywords are also garbled with randomness in order to hide actual query/result statistics. Our security analysis and experiment on request for comments database ensure the security and efficiency of CSA-CSE. |
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Article |
author |
Ahsan, M. A. Manazir Ali, Ihsan Idris, Mohd Yamani Idna Imran, Muhammad Shoaib, Muhammad |
author_facet |
Ahsan, M. A. Manazir Ali, Ihsan Idris, Mohd Yamani Idna Imran, Muhammad Shoaib, Muhammad |
author_sort |
Ahsan, M. A. Manazir |
title |
Countering statistical attacks in cloud-based searchable encryption |
title_short |
Countering statistical attacks in cloud-based searchable encryption |
title_full |
Countering statistical attacks in cloud-based searchable encryption |
title_fullStr |
Countering statistical attacks in cloud-based searchable encryption |
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Countering statistical attacks in cloud-based searchable encryption |
title_sort |
countering statistical attacks in cloud-based searchable encryption |
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Springer/Plenum Publishers |
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2020 |
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http://eprints.um.edu.my/36627/ |
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1809136909210877952 |
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13.19449 |