Compressed Oblivious Encoding for Homomorphically Encrypted Search
Seung Geol Choi, Dana Dachman-Soled, S. Dov Gordon, Linsheng Liu,, Arkady Yerukhimovich

TL;DR
This paper introduces a novel compressed oblivious encoding scheme that significantly enhances the efficiency of homomorphic encryption-based secure search, enabling parallel retrieval of multiple items with reduced computational complexity.
Contribution
The authors propose a new framework that retrieves all matching items in parallel, eliminates homomorphic multiplications for index computation, and demonstrates substantial speed-ups over previous methods.
Findings
Achieves 1800X speed-up in fetching 16 records
Reduces search complexity by avoiding homomorphic multiplications
Enables parallel retrieval of multiple matching items
Abstract
Fully homomorphic encryption (FHE) enables a simple, attractive framework for secure search. Compared to other secure search systems, no costly setup procedure is necessary; it is sufficient for the client merely to upload the encrypted database to the server. Confidentiality is provided because the server works only on the encrypted query and records. While the search functionality is enabled by the full homomorphism of the encryption scheme. For this reason, researchers have been paying increasing attention to this problem. Since Akavia et al. (CCS 2018) presented a framework for secure search on FHE encrypted data and gave a working implementation called SPiRiT, several more efficient realizations have been proposed. In this paper, we identify the main bottlenecks of this framework and show how to significantly improve the performance of FHE-base secure search. In particular,…
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