Secure, Dynamic, and Efficient Keyword Search With Flexible Merging for Cloud Storage

In this paper, we propose a Mergeable Searchable Symmetric Encryption (MSSE) scheme to enable secure keyword search and updates over encrypted cloud data. Particularly, MSSE allows flexible keyword merging, where users can remotely merge file identifiers associated with keywords to create new keyword-to-file identifier relationships. The function is designed for a user to manage their outsourced data conveniently. To this end, we first introduce a new encrypted index where each keyword's relevant file identifiers are grouped, encoded, and encrypted with super-increasing sequences and homomorphic encryption. With such an index, users leverage Distributed Multi-point Functions (DMPFs) to achieve secure keyword search and merge, maintaining efficiency while ensuring high privacy. To address the issue of maintaining “merging consistency” between pre-merged entries and newly updated entries, we employ the DMPF on clusters that incorporate the updated files. The approach significantly minimizes client-side computational overhead compared to re-executing the entire keyword merging process. We formally prove that MSSE can achieve parallel privacy. Extensive performance evaluation shows that MSSE is efficient in terms of computational and communication overheads.

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Publication Details

Journal
IEEE Transactions on Services Computing
Published
2024-08-13
DOI
https://doi.org/10.1109/tsc.2024.3442558
Citations
4
Primary Topic
Cloud Data Security Solutions
Type
article
Field-Weighted Citation Impact
3.12

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article

Secure, Dynamic, and Efficient Keyword Search With Flexible Merging for Cloud Storage

Ye Su, Cheng Huang, Jing Qin, Xi Zhang
4 citations
IEEE Transactions on Services Computing
Cloud Data Security Solutions
3.12
article

Secure, Dynamic, and Efficient Keyword Search With Flexible Merging for Cloud Storage

Ye Su, Cheng Huang, Jing Qin, Xi Zhang
article en
4 citations

Abstract

In this paper, we propose a Mergeable Searchable Symmetric Encryption (MSSE) scheme to enable secure keyword search and updates over encrypted cloud data. Particularly, MSSE allows flexible keyword merging, where users can remotely merge file identifiers associated with keywords to create new keyword-to-file identifier relationships. The function is designed for a user to manage their outsourced data conveniently. To this end, we first introduce a new encrypted index where each keyword's relevant file identifiers are grouped, encoded, and encrypted with super-increasing sequences and homomorphic encryption. With such an index, users leverage Distributed Multi-point Functions (DMPFs) to achieve secure keyword search and merge, maintaining efficiency while ensuring high privacy. To address the issue of maintaining “merging consistency” between pre-merged entries and newly updated entries, we employ the DMPF on clusters that incorporate the updated files. The approach significantly minimizes client-side computational overhead compared to re-executing the entire keyword merging process. We formally prove that MSSE can achieve parallel privacy. Extensive performance evaluation shows that MSSE is efficient in terms of computational and communication overheads.

IEEE Transactions on Services ComputingVol. 17(5)
Shandong University (CN), Fudan University (CN), Shandong Normal University (CN), Hebei Normal University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shandong Province
Openalex Percentile: Top 7%
Cloud Data Security Solutions
3.12
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Secure, Dynamic, and Efficient Keyword Search With Flexible Merging for Cloud Storage — Ye Su, Cheng Huang, et al. · IEEE Transactions on Services Computing (2024) | TGRS Research Map | TGRS