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Cybersecurity technology - Security specification for generative artificial intelligence pre-training and fine-tuning data
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Basic data
| Standard ID | GB/T 45652-2025 (GB/T45652-2025) |
| Description (Translated English) | Cybersecurity technology - Security specification for generative artificial intelligence pre-training and fine-tuning data |
| Sector / Industry | National Standard (Recommended) |
| Classification of Chinese Standard | L80 |
| Classification of International Standard | 35.030 |
| Word Count Estimation | 22,213 |
| Date of Issue | 2025-04-25 |
| Date of Implementation | 2025-11-01 |
| Issuing agency(ies) | State Administration for Market Regulation, China National Standardization Administration |
GB/T 45652-2025: Cybersecurity technology - Security specification for generative artificial intelligence pre-training and fine-tuning data
---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order.
ICS 35.030
CCSL80
National Standard of the People's Republic of China
Cybersecurity Technology Generative AI Pre-training
and optimize training data security specifications
Released on 2025-04-25
2025-11-01 Implementation
State Administration for Market Regulation
The National Standardization Administration issued
Table of contents
Preface III
Introduction IV
1 Scope 1
2 Normative references 1
3 Terms and Definitions 1
4 General safety requirements 2
5 Security requirements for pre-training data processing activities 3
5.1 Data Collection 3
5.2 Data Preprocessing 3
5.3 Data Usage 4
6 Optimizing security requirements for training data processing activities 4
6.1 Data Collection 4
6.2 Data Preprocessing 5
6.3 Data Usage 5
7 Evaluation Methods 5
7.1 General safety assessment method 5
7.2 Evaluation Methods for Pre-training Data Processing Activities 7
7.2.1 Data Collection 7
7.2.2 Data Preprocessing 8
7.2.3 Data usage 10
7.3 Optimizing the evaluation method of training data processing activities 10
7.3.1 Data Collection 10
7.3.2 Data Preprocessing 11
7.3.3 Data Usage 12
Reference 14
Foreword
This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for standardization work Part 1.Structure and drafting rules for standardization documents"
Drafting.
Please note that some of the contents of this document may involve patents. The issuing organization of this document does not assume the responsibility for identifying patents.
This document was proposed and coordinated by the National Cybersecurity Standardization Technical Committee (SAC/TC260).
This document was drafted by. Beijing Zhongguancun Laboratory, National Computer Network Emergency Response Technical Processing Coordination Center, China Electronics Technology Standards
Institute of Chemistry, Peking University, Beijing Topsec Network Security Technology Co., Ltd., Beijing Kuaishou Technology Co., Ltd., Alibaba (Beijing) Software
Services Co., Ltd., Beijing Baidu Netcom Technology Co., Ltd., Tsinghua University, Beijing Ruilai Smart Technology Co., Ltd., Tianyi Security Technology Co., Ltd.
Company, China Mobile Communications Group Co., Ltd., Xiaomi Technology Co., Ltd., Alibaba Cloud Computing Co., Ltd., Beijing Mianbi Intelligent Technology Co., Ltd.
Ltd., Hangzhou EZVIZ Software Co., Ltd., Beijing Institute of Technology, Beijing Zero One Everything Technology Co., Ltd., Institute of Automation, Chinese Academy of Sciences
Institute, Lenovo (Beijing) Co., Ltd., Beijing Qihoo Technology Co., Ltd., iFlytek Co., Ltd., Huawei Cloud Computing Technology Co., Ltd.
Beijing Shuanxing Technology Co., Ltd., the Third Research Institute of the Ministry of Public Security, Ant Technology Group Co., Ltd., Beijing Venusstar Information Security Co., Ltd.
Technology Co., Ltd., Institute of Computing Technology, Chinese Academy of Sciences.
The main drafters of this document are. Xu Ke, Yao Long, Zhang Zhen, Liu Yong, Tan Zhixing, Li Qi, Xie Anming, Xu Xiaogeng, Yang Guang, Cui Tianyu, Hao Chunliang,
Zhang Yanting, Xue Zhihui, Guo Jianling, Gu Chen, Jiang Wen, Ye Xiaojun, Tian Tian, Liang Wei, Jiang Weiqiang, Li Jiakun, Peng Juntao, Wang Huadong, Zheng Hongdong,
Hong Yanqing, Wang Haitang, Zhu Guibo, Meng Yao, Zhang Xiangzheng, Liu Junhua, Li Fengfeng, Liu Yuhong, Liu Nan, Lin Guanchen, Wang Yan, Luo Hongwei, Tan Yingshui,
Zhang Feng, Sun Xudong, Du Jinhao, Xu Shizhen, An Peng, Yu Yang, Sun Yong, Guo Jiexin, Wu Jianliang, Wang Xia, Wang Jinqiao, Gao Boya, Guan Ming, Wang Shijin,
Zhao Lili, Wang Wenyu, Ding Zhiguo, Jiang Faqun, Sheng Qiang, and Wu Bowen.
Introduction
Pre-training and optimizing training data are the foundation of generative artificial intelligence and directly determine the quality and security level of generated content.
Pre-training and optimization of training data have security risks in the collection, pre-processing, and use of processing activities, and standards and specifications are urgently needed to improve pre-training
Training and optimizing the security level of training data.
Cybersecurity Technology Generative AI Pre-training
and optimize training data security specifications
1 Scope
This document specifies the security requirements for generative artificial intelligence pre-training and optimization training data and its processing activities, and describes the corresponding evaluation
Price method.
This document applies to generative artificial intelligence service providers to carry out pre-training and optimization training data processing activities and security self-assessment.
It is also suitable for third-party organizations to conduct security assessments on pre-training and optimized training data.
2 Normative references
The contents of the following documents constitute essential clauses of this document through normative references in this document.
For referenced documents without a date, only the version corresponding to that date applies to this document; for referenced documents without a date, the latest version (including all amendments) applies to
This document.
GB/T 35273 Information security technology Personal information security specification
GB/T 41479-2022 Information security technology - Security requirements for network data processing
3 Terms and definitions
The following terms and definitions apply to this document.
3.1
Use generative artificial intelligence technology to provide the public with services that generate text, images, audio, video and other content.
[Source. GB/T 45654-2025, 3.1]
3.2
Service Provider serviceprovider
Organizations or individuals that provide generative artificial intelligence services in the form of interactive interfaces, programmable interfaces, etc.
3.3
Service User serviceuser
Organizations or individuals using generative AI services.
3.4
pre-training
The training process of using large-scale data to enable generative artificial intelligence models to acquire general knowledge.
3.5
Fine-tuning
Based on pre-training, the training process uses specific domain data to enable the generative artificial intelligence model to acquire domain-oriented service capabilities.
Note. Specific areas are not limited to a certain professional field and usually cover multiple fields.
...
