Artificial Intelligence Security Standardization White Paper, Section 5 ("Recommendations for AI security standardization work")

Summary

Launch AI security standardization work by coordinating a system of AI security standards, focusing on foundational and application-specific research.

Accelerate development of AI security standards in key areas, driven by urgent needs and safety incidents, to address security risks and ethical issues.

Promote the application of AI security standards through pilot mechanisms and collaboration between academia, industry, and research institutions.

Strengthen training for AI security standardization talent by establishing multi-level training programs and fostering collaboration among universities, research institutes, and enterprises.

Participate actively in international AI security standardization by aligning Chinese efforts with global achievements, enhancing China's influence, and facilitating international cooperation.

Establish an early warning mechanism for high-security-risk AI technologies and products, including a catalog of risks and management standards.

Improve AI security supervision by developing an index evaluation system, enhancing AI supply chain security management, and formulating supportive standards.

Recommends launching and coordinating AI security standardization work for enhanced system improvement.

5 Recommendations for AI security standardization work (1) Attach importance to improving a system of AI security standards We recommend launching AI standardization work, coordinating the planning of a system of AI security standards, strengthening research into fundamental AI security standards, and deepening the work of AI application security standards.

Recommends investigating AI security standardization needs and prioritizing research on comprehensive AI security standards.

The first is the overall planning of a system of AI security standards. In order to ensure the orderly progress of the development of AI security standards, we recommend investigating and analyzing the need for AI security standardization in China and giving priority to research on a system of AI security standards. The system of standards should cover the security needs of multiple objects such as the foundation, platform, technology, products, and applications of AI and should be able to clearly define relationships with related standards such as big data security, personal information protection, cloud computing security, and IoT security.

Emphasizes addressing AI algorithm discrimination and bias, developing ethical principles, and guiding standards implementation.

Second, pay close attention to research and to implement the AI ethical principles. Focus on the outstanding issues of AI algorithm discrimination and algorithmic bias. Analyze and review the ethical needs of AI in various scenarios, develop and refine AI ethical principles, and guide the implementation of principles and requirements related to AI standards.

Accelerates AI security standard development, focusing on emergency-driven standards in key areas.

(2) Accelerate the development of standards in key areas AI has the characteristics of wide coverage, complex application scenarios, and many types of security requirements. We recommend that AI security standardization promotion plans be established to develop AI security standards in accordance with the concept of “emergency use first, driven by safety incidents.” The development of standards should be accelerated in key areas, and AI security standardization should be advanced in an orderly fashion.

Recommends strengthening AI security standards, focusing on monitoring, risk assessment, ethical design, and data security.

First is fundamental AI security standards research. China’s AI security standards mainly focus on the field of application security, lacking security standards for AI itself or basic commonality. We recommend that fundamental AI security standards be strengthened with requirements for AI security aspects such as monitoring and early warning, risk assessment, security accountability, and research personnel security guidelines based on the New Generation Artificial Intelligence Development Plan. Standards research should be conducted for such aspects as AI security reference architecture, security risks, ethical design, and security assessment to grasp AI algorithm security threats and protection needs to clarify general algorithm security principles and requirements and to strengthen AI algorithm model security and robustness. AI algorithm models and smart product security requirements and evaluation methods should be standardized to address the data quality and dataset security issues faced by AI.

Recommends advancing smart product security standards before AI application standards for enhanced security.

Second is a deepening of AI application security standards. Given that AI is becoming ever more integrated with various application fields, we should begin to study AI products and application security standards. We recommend that smart product security standards be ahead of AI application standards. AI security standardization characteristics and requirements should be extracted based on the development of standards for smart door locks, smart homes, and other fields that have been carried out by the National Information Security Standardization Technical Committee.

Prioritizes areas with urgent standardization needs and develops AI security standards for improved safety.

Afterwards, we should give priority to areas where there is an urgent need for standardization, more mature applications, urgent security needs, wide applications, or areas that are relatively sensitive. We should develop AI products and application security standards to improve the security requirements of existing AI standards.

Recommends prioritizing AI security standards addressing urgent security needs and mature applications.

Third is to develop standards according to the concept of “fulsome research, with priority to urgent needs, driven by security incidents.” We recommend that priority be given to security standards with pressing security needs and mature applications. For instance, standards such as Artificial Intelligence Security Reference Framework, Artificial Intelligence Dataset Security, Artificial Intelligence Data Labeling Security, Machine Learning Algorithm Model Trustworthiness, Artificial Intelligence Open Source Framework Security, Artificial Intelligence Application Security Guide, and Artificial Intelligence Security Service Capabilities Requirements should be prioritized.

Promotes research on AI security standards alongside risk assessment and key AI product standards.

Simultaneously, research work on fundamental AI standards should be conducted with the study and application of security risk assessment standards and key AI product and service security standards such as smart manufacturing and intelligent networked vehicles. We should gradually promote research on AI security standards in other fields.

Promotes the application of AI security standards to address risks and explore standardization paths.

(3) Diligently promote the application of AI security standards In order to improve the effectiveness and operability of AI security standards, address prominent AI security risks, and explore a path to standardization of the most difficult and pressing issues of AI security, we recommend that in-depth application and practical work be carried out for AI security standards.

Improves pilot mechanisms for AI security standards implementation and evaluation to enhance standardization development.

First, improve the pilot mechanisms for AI security standards. Select a number of pilot enterprises to carry out an evaluation of the applicability of the standards and the effectiveness of implementation, establish the concept of work of “tracking practice, discovering issues, summarizing experiences, improving standards, and providing feedback for the next step of standardization,” and promote the rapid and high-quality development of AI security standardization.

Improves AI security standards by integrating industry, university, and research for joint development and application.

Second, improve the research, promotion, and application of promotion mechanisms for AI security standards. Organize universities, scientific research institutes, and enterprises in jointly breaking past AI security standardization difficulties, give play to the advantages of various institutions, establish AI security standards research, promotion, and application mechanisms that integrate "industry, university, and research," and promote the benign development of the AI industry.

Recommends establishing and improving a multi-level AI security standardization talent training mechanism.

(4) Effectively strengthen the training of AI security standardization talent Talent is the cornerstone of AI security standardization work, and we recommend that a multi-level and multi-type AI security talent training mechanism be established and improved upon.

Establish training programs for technology standards, publicity, habituation, and evaluation for AI security professionals.

First, train AI security professionals. Establish training programs for professional technology, standard setting, publicity and habituation training (宣贯培训), and testing and evaluation.

Encourages collaboration and explores training paths integrating talent into AI security.

Second, encourage universities, research institutes, and enterprises to establish collaboration. Explore training paths that integrate talent into AI security.

Strengthens support for AI security projects and optimizes resources to address key security issues.

Third, strengthen support for artificial intelligence security and standardization projects. Optimize the ratio of scientific research resources and management and evaluation mechanisms to ensure that relevant talent fields concentrate on solving key AI security issues.

Encourages incorporating international AI security standards with China's specific needs and characteristics.

(5) Actively participate in international AI security standardization International organizations such as ISO and IEEE have organized and undertaken a number of AI security standardization research tasks and have achieved certain standardization results in some areas. We recommend that the achievements of international and overseas standardization work be fully digested, absorbed, and incorporated with China's AI security needs in order to explore AI security standardization work paths with Chinese characteristics.

Tracks AI security standardization trends, consolidates research, absorbs overseas experience, and promotes China's development.

First, closely track and study the dynamics and development trends of AI security standardization work at home and abroad. Consolidate the research achievements of international AI security standardization, absorb the experiences of standards development overseas, and promote the better development of AI security standardization in China.

Enhances China's AI security standards influence internationally and supports Chinese experts in standardization roles.

Second, continuously enhance the influence of China's international standards in the field of AI security. Diligently support the participation of Chinese institutions and experts in international standardization work, strengthen research into AI security standards, and encourage Chinese experts to serve in international standardization organizations and act as editors of international standard projects.

Establish standards cooperation mechanisms for AI security using China's international exchange efforts.

Third, give full play to China's international standardization exchange and cooperation mechanisms. Given the rich application scenarios of China's AI industry, standards cooperation and exchange mechanisms in the field of AI security should be established to enrich the achievements of Chinese AI security standardization work with the help of international and overseas efforts.

Recommends establishing an early warning mechanism for high-security risk AI technologies and applications.

(6) Establish an AI high security risk early warning mechanism as soon as possible In view of AI technologies, products, and applications with high security risks, we recommend that an early warning mechanism be studied and proposed for highly dangerous AI security risks.

Establishes a catalog of highly dangerous AI security risks and classifies high-impact risk items.

First, establish a catalog of highly dangerous AI security risks. Review AI technologies, products, and applications with outstanding security risks that may create high-impact security issues and classify and categorize risk items within the catalog.

Establishes an AI high security risk early warning mechanism with a comprehensive risk early warning plan.

Second, establish an AI high security risk early warning mechanism. Incorporate technology, application, and product characteristics and propose an early warning plan for risks.

Formulates AI safety risk management standards for risk identification, analysis, and processing.

Third, study and formulate highly dangerous AI safety risk management standards. Starting with standards, propose a security risk management plan for highly dangerous AI that incorporates techniques, management, evaluation, and other means and covers such aspects as risk identification, analysis, and processing.

Recommends developing AI security standards and monitoring systems to prevent illegal or improper AI use.

(7) Effectively improve AI security supervision support capabilities Standardization can strongly support the implementation of AI security supervision, and we recommend the development of an index evaluation system for AI security standards. First, establish a sound AI supervision system and formulate supporting standards. The government should use standards as a powerful starting point to establish a monitoring system that runs through the entire cycle of AI development, design, data acquisition, and market application to prevent AI from being used illegally or used in areas that deviate from its intended purpose.

Recommends accelerating AI supply chain security research and developing standards for key industry applications.

Second, we recommend accelerating research into AI supply chain security management mechanisms. Develop supporting standards for AI supply chain security, propose AI supply chain procurement requirements for telecommunications, energy, transportation, power, finance, and other industries, and promote the piloting of relevant standards in key areas to provide a useful reference for Chinese party and government departments, and for key industries, to manage AI supply chain security risks and offer practical guidance for enterprises as they strengthen AI supply chain management.