Paper 2024/2041 Original: eprint.iacr.org/2024/2041 ↗

SeaSearch: Secure and Efficient Selection Queries

Shantanu Sharma
Yin Li
Sharad Mehrotra
Nisha Panwar
Komal Kumari
Swagnik Roychoudhury
Abstract

Information-theoretic or unconditional security provides the highest level of security --- independent of the computational capability of an adversary. Secret-sharing techniques achieve information-theoretic security by splitting a secret into multiple parts (called shares) and storing the shares across non-colluding servers. However, secret-sharing-based solutions suffer from high overheads due to multiple communication rounds among servers and/or information leakage due to access-patterns (i.e.., the identity of rows satisfying a query) and volume (i.e., the number of rows satisfying a query). We propose SeaSearch, an information-theoretically secure approach that uses both additive and multiplicative secret-sharing, to efficiently support a large class of selection queries involving conjunctive, disjunctive, and range conditions. Two major contributions of SeaSearch are: (i) a new search algorithm using additive shares based on fingerprints, which were developed for string-matching over cleartext; and (ii) two row retrieval algorithms: one is based on multiplicative shares and another is based on additive shares. SeaSearch does not require communication among servers storing shares and does not reveal any information to an adversary based on access-patterns and volume.

Metadata
Available format(s)
PDF
Category
Applications
Publication info
Preprint.
History
2024-12-18: last updated
2024-12-18: published
Short URL
https://ia.cr/2024/2041
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2024/2041,
      author = {Shantanu Sharma and Yin Li and Sharad Mehrotra and Nisha Panwar and Komal Kumari and Swagnik Roychoudhury},
      title = {SeaSearch: Secure and Efficient Selection Queries},
      howpublished = {Cryptology {ePrint} Archive, Paper 2024/2041},
      year = {2024},
      url = {https://eprint.iacr.org/2024/2041}
}
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