Owner-free Distributed Symmetric Searchable Encryption supporting Conjunctive queries
Symmetric Searchable Encryption (SSE), as an ideal primitive, can ensure data privacy while supporting retrieval over encrypted data. However, existing multi-user SSE schemes require the data owner to share the secret key with all query users or always be online to generate search tokens. While ther...
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| Main Authors: | , , , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2023
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/8465 https://ink.library.smu.edu.sg/context/sis_research/article/9468/viewcontent/Owner_free_DSSE_av.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Symmetric Searchable Encryption (SSE), as an ideal primitive, can ensure data privacy while supporting retrieval over encrypted data. However, existing multi-user SSE schemes require the data owner to share the secret key with all query users or always be online to generate search tokens. While there are some solutions to this problem, they have at least one weakness, such as non-supporting conjunctive query, result decryption assistance of the data owner, and unauthorized access. To solve the above issues, we propose an Owner-free Distributed Symmetric searchable encryption supporting Conjunctive query (ODiSC). Specifically, we first evaluate the Learning-Parity-with-Noise weak Pseudorandom Function (LPN-wPRF) in dual-cloud architecture to generate search tokens with the data owner free from sharing key and being online. Then, we provide fine-grained conjunctive query in the distributed architecture using additive secret sharing and symmetric-key hidden vector encryption. Finally, formal security analysis and empirical performance evaluation demonstrate that ODiSC is adaptively simulation-secure and efficient. |
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