人工智能安全治理白皮书（2025）

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The rapid development of artificial intelligence (AI) technology is transforming global industrial patterns and driving the fourth industrial revolution, but it also brings multiple security risks related to data, models, infrastructure, and applications [7][8] - The white paper aims to establish a safe, reliable, fair, and trustworthy AI system, focusing on AI security governance, risk analysis, and the development of a governance framework [8][9] - The report emphasizes the need for a comprehensive governance system that includes legal regulations, standards, and management measures to ensure the safe and controllable development of AI technology [20][22] Summary by Sections AI Overview - AI technology has evolved from symbolic rules to machine learning and deep learning, with significant growth in large language models (LLMs) driving technological progress and industrial upgrades [11][12] - Major companies in both domestic and international markets are expanding the application of large models across various industries, enhancing AI technology's development and industrial intelligence [12][13] AI Security Governance Risk Analysis and Challenges - AI security governance risks include vulnerabilities inherent to AI and external threats faced during application, categorized into infrastructure, data, model algorithm, and application security risks [29][30] - Specific risks include hardware device security, cloud security, model-as-a-service platform security, and computational network security [31][32][33][37] AI Security Governance System - The governance system consists of a four-part supervisory and management framework, focusing on infrastructure, model, data, and application security [20][22] - The report outlines the importance of addressing security at all levels to build a truly secure AI ecosystem [22] AI Security Technology Solutions - The report discusses various technical solutions and case studies across AI infrastructure, data, models, and applications to enhance security governance [8][9] AI Security Development Recommendations - Recommendations include establishing a legal framework, building a standard system, exploring cutting-edge technologies, and fostering talent through industry-academia collaboration [8][9]