TY - GEN
T1 - HE3DB
T2 - 30th ACM SIGSAC Conference on Computer and Communications Security, CCS 2023
AU - Bian, Song
AU - Zhang, Zhou
AU - Pan, Haowen
AU - Mao, Ran
AU - Zhao, Zian
AU - Jin, Yier
AU - Guan, Zhenyu
N1 - Publisher Copyright:
© 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM
PY - 2023/11/21
Y1 - 2023/11/21
N2 - As concerns are increasingly raised about data privacy, encrypted database management system (DBMS) based on fully homomorphic encryption (FHE) attracts increasing research attention, as FHE permits DBMS to be directly outsourced to cloud servers without revealing any plaintext data. However, the real-world deployment of FHE-based DBMS faces two main challenges: i) high computational latency, and ii) lack of elastic query processing capability, both of which stem from the inherent limitations of the underlying FHE operators. Here, we introduce HE3DB, a fully homomorphically encrypted, efficient and elastic DBMS framework based on a new FHE infrastructure. By proposing and integrating new arithmetic and logic homomorphic operators, we devise fast and high-precision homomorphic comparison and aggregation algorithms that enable a variety of SQL queries to be applied over FHE ciphertexts, e.g., compound filter-aggregation, sorting, grouping, and joining. In addition, in contrast to existing encrypted DBMS that only support aggregated information retrieval, our framework permits further server-side elastic analytical processing over the queried FHE ciphertexts, such as private decision tree evaluation. In the experiment, we rigorously study the efficiency and flexibility of HE3DB. We show that, compared to the state-of-the-art techniques, HE3DB can homomorphically evaluate end-to-end SQL queries as much as 41×-299× faster than the state-of-the-art solution, completing a TPC-H query over a 16-bit 10K-row database within 241 seconds.
AB - As concerns are increasingly raised about data privacy, encrypted database management system (DBMS) based on fully homomorphic encryption (FHE) attracts increasing research attention, as FHE permits DBMS to be directly outsourced to cloud servers without revealing any plaintext data. However, the real-world deployment of FHE-based DBMS faces two main challenges: i) high computational latency, and ii) lack of elastic query processing capability, both of which stem from the inherent limitations of the underlying FHE operators. Here, we introduce HE3DB, a fully homomorphically encrypted, efficient and elastic DBMS framework based on a new FHE infrastructure. By proposing and integrating new arithmetic and logic homomorphic operators, we devise fast and high-precision homomorphic comparison and aggregation algorithms that enable a variety of SQL queries to be applied over FHE ciphertexts, e.g., compound filter-aggregation, sorting, grouping, and joining. In addition, in contrast to existing encrypted DBMS that only support aggregated information retrieval, our framework permits further server-side elastic analytical processing over the queried FHE ciphertexts, such as private decision tree evaluation. In the experiment, we rigorously study the efficiency and flexibility of HE3DB. We show that, compared to the state-of-the-art techniques, HE3DB can homomorphically evaluate end-to-end SQL queries as much as 41×-299× faster than the state-of-the-art solution, completing a TPC-H query over a 16-bit 10K-row database within 241 seconds.
KW - Fully Homomorphic Encryption
KW - Secure Database Outsourcing
UR - https://www.scopus.com/pages/publications/85179843606
U2 - 10.1145/3576915.3616608
DO - 10.1145/3576915.3616608
M3 - 会议稿件
AN - SCOPUS:85179843606
T3 - CCS 2023 - Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security
SP - 2930
EP - 2944
BT - CCS 2023 - Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security
PB - Association for Computing Machinery, Inc
Y2 - 26 November 2023 through 30 November 2023
ER -