Operon

Author:

Wang Sheng1,Li Yiran1,Li Huorong1,Li Feifei1,Tian Chengjin1,Su Le1,Zhang Yanshan1,Ma Yubing1,Yan Lie1,Sun Yuanyuan1,Cheng Xuntao1,Xie Xiaolong1,Zou Yu1

Affiliation:

1. Alibaba Group

Abstract

The past decade has witnessed the rapid development of cloud computing and data-centric applications. While these innovations offer numerous attractive features for data processing, they also bring in new issues about the loss of data ownership. Though some encrypted databases have emerged recently, they can not fully address these concerns for the data owner. In this paper, we propose an ownership-preserving database (OPDB), a new paradigm that characterizes different roles' responsibilities from nowadays applications and preserves data ownership throughout the entire application. We build Operon to follow the OPDB paradigm, which utilizes the trusted execution environment (TEE) and introduces a behavior control list (BCL). Different from access controls that merely handle accessibility permissions, BCL further makes data operation behaviors under control. Besides, we make Operon practical for real-world applications, by extending database capabilities towards flexibility, functionality and ease of use. Operon is the first database framework with which the data owner exclusively controls its data across different roles' subsystems. We have successfully integrated Operon with different TEEs, i.e. , Intel SGX and an FPGA-based implementation, and various database services on Alibaba Cloud, i.e. , PolarDB and RDS PostgreSQL. The evaluation shows that Operon achieves 71% - 97% of the performance of plaintext databases under the TPC-C benchmark while preserving the data ownership.

Publisher

Association for Computing Machinery (ACM)

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. BiTDB: Constructing A Built-in TEE Secure Database for Embedded Systems;IEEE Transactions on Knowledge and Data Engineering;2024-09

2. Object-oriented Unified Encrypted Memory Management for Heterogeneous Memory Architectures;Proceedings of the ACM on Management of Data;2024-05-29

3. Survey of research on confidential computing;IET Communications;2024-04-23

4. Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense;Proceedings of the VLDB Endowment;2024-04

5. TEE-based General-purpose Computational Backend for Secure Delegated Data Processing;Proceedings of the ACM on Management of Data;2023-12-08

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