App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 4

Review of privacy protection technologies in retrieval-augmented generation

Liu Xiaoqian1
Yuan Ming1,2
Qian Hanwei1,3
Gao Guangliang1
Wang Qun1
1. Dept. of Computer Information and Cyber Security, Jiangsu Police Institute, Nanjing 210031, China
2. School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
3. Software Institute, Nanjing University, Nanjing 210093, China
DOI: 10.19734/j.issn.1001-3695.2025.09.0308

Abstract

Retrieval-Augmented Generation (RAG) systems face severe risks of sensitive information leakage throughout the entire retrieval and generation process. To systematically sort out their privacy threats and protection technologies, this study first explains the core principles and application scenarios of RAG systems and clarifies their privacy definition. It systematically analyzes representative privacy attack models such as membership inference, implicit knowledge extraction, and knowledge poisoning. Then, it classifies existing privacy protection technologies into four categories: first, differential privacy technologies based on noise injection; second, decentralized collaborative training frameworks based on federated learning; third, source-level privacy substitution scheme based on synthetic data; fourth, encryption technologies covering the entire data lifecycle. By comparing the applicable scenarios, advantages and limitations of various technologies, this study aims to provide strategic references for privacy protection of RAG systems.

Foundation Support

国家自然科学基金资助项目(72401110)
2023年江苏高校"青蓝工程"优秀青年骨干教师项目
江苏省高等教育教改研究项目(2023JSJG364)
江苏省高校哲学社会科学研究项目(2023SJYB0468)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.09.0308
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 4

Publish History

[2025-12-18] Accepted Paper

Cite This Article

刘晓迁, 袁明, 钱汉伟, 等. 检索增强生成中的隐私保护技术综述 [J]. 计算机应用研究, 2026, 43 (4). (2025-12-19). https://doi.org/10.19734/j.issn.1001-3695.2025.09.0308. (Liu Xiaoqian, Yuan Ming, Qian Hanwei, et al. Review of privacy protection technologies in retrieval-augmented generation [J]. Application Research of Computers, 2026, 43 (4). (2025-12-19). https://doi.org/10.19734/j.issn.1001-3695.2025.09.0308. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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