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GB/T 41773-2022 English PDF

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GB/T 41773-2022: Information security technology - Security requirements of gait recognition data
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Basic data

Standard ID GB/T 41773-2022 (GB/T41773-2022)
Description (Translated English) Information security technology - Security requirements of gait recognition data
Sector / Industry National Standard (Recommended)
Classification of Chinese Standard L80
Classification of International Standard 35.030
Word Count Estimation 14,118
Date of Issue 2022-10-14
Date of Implementation 2023-05-01
Issuing agency(ies) State Administration for Market Regulation, China National Standardization Administration

GB/T 41773-2022: Information security technology - Security requirements of gait recognition 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.
Information security technology -- Security requirements of gait recognition data ICS 35.030 CCSL80 National Standards of People's Republic of China Information security technology gait recognition data security requirements Published on 2022-10-12 2023-05-01 Implementation State Administration for Market Regulation Released by the National Standardization Administration directory Preface I 1 Scope 1 2 Normative references 1 3 Terms and Definitions 1 4 Overview 2 4.1 Gait recognition data activity 2 4.2 Typical scenarios of gait recognition 2 4.3 Gait recognition data activity security risks 3 5 Basic Safety Requirements 3 6 Data collection 3 7 Data Storage and Transmission 4 8 Data usage 4 9 Data processing, provision and disclosure5 10 Data deletion5 Appendix A (Informative) Common Security Risks for Gait Recognition Data6 A.1 Security Risk Description 6 A.2 Common security risks and terms comparison table 6 Appendix B (Informative) Example of Informed Consent Form for Scientific Experiment Scenario 8 Reference 10

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 of Standardization Documents" drafted. Please note that some content of this document may be patented. The issuing agency of this document assumes no responsibility for identifying patents. This document is proposed and managed by the National Information Security Standardization Technical Committee (SAC/TC260). This document is drafted by. Galaxy Waterdrop Technology (Beijing) Co., Ltd., China Electronics Standardization Institute, Chinese Academy of Sciences Automation Research Institute, Harbin Engineering University, Beijing University of Posts and Telecommunications, Beijing Qihoo Technology Co., Ltd., the First Research Institute of the Ministry of Public Security, China Information and Communication Research Institute Research Institute, National Industrial Information Security Development Research Center, Ant Technology Group Co., Ltd., Beijing Police Academy, National Computer Network Application Emergency Technical Handling Coordination Center, Daily Interactive Co., Ltd., OPPO Guangdong Mobile Communications Co., Ltd., Ministry of Public Security Physical Evidence Identification Center, Southern University of Science and Technology, Beijing Deyi Yintong Technology Co., Ltd., and Huawei Technologies Co., Ltd. The main drafters of this document. Huang Yongzhen, Liu Qiyun, Hao Chunliang, Zhang Man, Cao Chunshui, Gu Xiaoxia, Li Wenying, Hu Ying, Xu Xiaogeng, Wang Liang, Wang Kejun, Lu Qi, Zhang Yi, Liu Dongni, Huang Yan, Fu Shan, He Zhaofeng, Liu Caiyun, Sun Yan, Lin Guanchen, Wu Honghao, Zhao Yunwei, Dong Lin, Fang Yi, Yang Minghui, Ye Fangjian, Yu Shiqi, Wu Xiaojun, Huang Xiaoni, Yan Minrui, Jin Chen, Wang Bingzheng, Huang Xinbei. Information security technology gait recognition data security requirements

1 Scope

This document specifies the security of gait recognition data collection, storage, transmission, use, processing, provision, disclosure, deletion and other data processing activities Require. This document applies to gait recognition data processors to regulate data processing activities, regulatory authorities, third-party evaluation agencies to gait recognition data Processing activities are monitored, managed, and evaluated for reference use.

2 Normative references

The contents of the following documents constitute essential provisions of this document through normative references in the text. Among them, dated citations documents, only the version corresponding to that date applies to this document; for undated references, the latest edition (including all amendments) applies to this document. GB/T 25069 Information Security Technical Terminology GB/T 35273 Information Security Technology Personal Information Security Specification GB/T 37988 Information Security Technology Data Security Capability Maturity Model GB/T 39335 Information Security Technology Personal Information Security Impact Assessment Guide GB/T 40660 Information Security Technology Basic Requirements for Biometric Information Protection GB/T 41479 Information Security Technology Network Data Processing Security Requirements

3 Terms and Definitions

GB/T 25069, GB/T 35273, GB/T 37988, GB/T 40660 and GB/T 41479 and the following terms and definitions applies to this document. 3.1 gait recognition A technology for identifying natural persons based on the biological characteristics and behavioral characteristics of natural persons contained in gait. Note. In addition to the application scenarios of identification, gait recognition can also be used in non-identification application scenarios, such as behavior analysis, posture analysis or anomaly analysis. 3.2 gait sample gaitsample Gait videos or image sequences of natural persons obtained through collection, preprocessing, etc. Note. The gait sample contains the raw (cut) video or continuous image sequence of the gait cycle of a natural person, and contains information such as clothing, shoes and hats, and carrying objects. 3.3 Gait silhouettes gaitsilhouettes The sequence of gait samples after segmentation. Note. After the gait sample is processed, the gait silhouette can be obtained, and it is also possible to obtain a sequence of human body parts segmentation images, a sequence of three-dimensional human body models, etc. Gait silhouette usually It is a black and white image, the body area is white, and the background area is black. 3.4 gait feature Data extracted from gait silhouettes for alignment.

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