Research Article
Research on Homomorphic Retrieval Method of Private Database Secrets in Multi-server Environment
@INPROCEEDINGS{10.1007/978-3-030-94185-7_17, author={Fu-lian Zhong and Jin-hua Liu}, title={Research on Homomorphic Retrieval Method of Private Database Secrets in Multi-server Environment}, proceedings={IoT and Big Data Technologies for Health Care. Second EAI International Conference, IoTCare 2021, Virtual Event, October 18-19, 2021, Proceedings, Part I}, proceedings_a={IOTCARE}, year={2022}, month={6}, keywords={Multi-server environment Privacy database Secret homomorphism Data retrieval}, doi={10.1007/978-3-030-94185-7_17} }- Fu-lian Zhong
Jin-hua Liu
Year: 2022
Research on Homomorphic Retrieval Method of Private Database Secrets in Multi-server Environment
IOTCARE
Springer
DOI: 10.1007/978-3-030-94185-7_17
Abstract
The traditional homomorphism retrieval method of privacy database is very complicated. In order to reduce the running time, this paper designs a homomorphic secret retrieval method for private database in multi-server environment. After the establishment of the secret homomorphism vector model, the semantic classification of the secret homomorphism ciphertext is carried out. Then, according to the characteristics of the neighborhood structure, the mapping interval is divided, and the HASH function is used to perform operations in the mapping interval. This process can reduce the computational complexity of the secret homomorphic ciphertext. Finally, a secret homomorphic retrieval model is established and an optimized retrieval algorithm is designed. Design experiments and compare the three conventional retrieval methods. According to the experimental data, in different mapping intervals, the average retrieval time of this method is 14.32 s, while the average retrieval time of the three control groups is 23.74 s, 29.03 s, At 20.92 s, the retrieval time of this method is shorter than that of the conventional method, which makes the homomorphic retrieval method of private databases more concise.
