k-Anonymously Private Search over Encrypted Data

2017/03/24 by Shiyu Ji, Kun Wan, Ji, Shiyu +1
Computer Science · #Complexity and Algorithms in Graphs #Cryptography and Data Security #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Privacy-Preserving Technologies in Data

paper · pdf · doi:10.48550/arxiv.1703.08269

openalex publication_date 2017/03/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper we compare the performance of various homomorphic encryption methods on a private search scheme that can achieve k-anonymity privacy. To make our benchmarking fair, we use open sourced cryptographic libraries which are written by experts and well scrutinized. We find that Goldwasser-Micali encryption achieves good enough performance for practical use, whereas fully homomorphic encryptions are much slower than partial ones like Goldwasser-Micali and Paillier.

Citations

• On lattices, learning with errors, random linear codes, and cryptography

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