# governance
標記為「governance」的 94 篇文章
審批工作流程繞過技術
於受治理代理系統中繞過人類與自動審批工作流程之技術。
專業級練習考試
25 題專業 AI 紅隊練習考試：演練方法論、範圍界定、報告撰寫、治理框架、客戶溝通與倫理考量。
模擬測驗 2:進階 AI 安全
涵蓋多模態攻擊、訓練管線安全、雲端 AI 安全、鑑識與治理的 25 題進階模擬測驗。
AI 治理模擬測驗
模擬測驗涵蓋EU AI Act、NIST frameworks、ISO standards、organizational 治理。
進階治理模擬測驗
模擬測驗涵蓋EU AI Act compliance、NIST AI 600-1 implementation、MITRE ATLAS mapping。
進階治理模擬測驗 (評估)
進階治理模擬測驗涵蓋international regulation、audit methodologies、organizational frameworks。
治理專家模擬測驗
Specialized 模擬測驗 focusing on AI 治理、compliance frameworks、audit methodologies。
EU AI Act Compliance 評估
綜合評估 of organizational readiness的EU AI Act requirements包括紅隊 testing mandates。
治理 & Compliance 評估
評估涵蓋EU AI Act、NIST AI RMF、ISO 42001、organizational AI 治理 frameworks。
治理評量
以 15 道中級題目測試你對 AI 治理、法規框架、合規要求與負責任 AI 實務的知識。
NIST AI RMF 評估
評估涵蓋implementation of NIST AI Risk Management Framework 跨 all four functions。
技能驗證: 治理 Audit
針對以下的實作驗證:AI 治理 audit skills包括 framework application、gap analysis。
技能驗證: 治理、Compliance
Verification of skills in AI 治理 framework implementation、audit、compliance 評估。
技能驗證: 治理 Audit (評估)
Practical verification of AI 治理 audit skills against EU AI Act、NIST AI RMF requirements。
治理認證 Prep Guide
學習指南的治理、compliance 認證涵蓋regulatory frameworks、standards。
專業實務學習指南
涵蓋 AI 紅隊方法論、作業管理、報告撰寫、治理框架與專業倫理的學習指南。
總結專案:實作 AI 合規框架
建置全面的 AI 合規框架,將安全測試對應至 EU AI Act、NIST AI RMF 與 ISO 42001 等監管要求。
Capstone:企業 AI 安全計畫
Capstone 演練:為大型組織設計並實作完整 AI 安全計畫,涵蓋治理、技術控制、事件回應與培訓。
Capstone:AI 治理稽核
Capstone 演練:進行涵蓋合規、風險與營運控制的完整 AI 治理稽核。
頂石專案:紅隊計畫設計
為虛構企業設計完整的 AI 紅隊計畫,產出完整的計畫章程文件。
Samsung 透過 ChatGPT 的程式碼外洩
分析 2023 年 4 月 Samsung 員工將專有原始碼、測試資料與內部會議筆記輸入 ChatGPT 所造成的事件。涵蓋資料外洩防護、可接受使用政策，以及企業 AI 治理。
雲端 AI 共同責任模型
AWS、Azure 與 GCP AI 服務的共同責任模型,釐清提供者與客戶的安全義務。
多雲 AI 安全概覽
多雲 AI 部署的安全風險：跨雲攻擊面、憑證管理挑戰、不一致的安全控制，以及 AWS、Azure 與 GCP AI 服務間的治理缺口。
多雲 AI 安全策略
為跨 AWS、Azure 與 GCP 的 AI 部署設計統一安全策略。
AI 程式碼生成的治理框架
管理 AI 程式碼生成風險的組織治理框架,涵蓋政策制定、風險評估、合規與成熟度模型。
AI 生成程式碼的授權合規
AI 生成程式碼的法律和合規風險，包括授權污染、版權暴露，以及程式碼生成工具的組織治理。
AI 稽核方法論
針對 AI 系統的結構化稽核方法論,涵蓋技術、組織與合規面向。
AI 稽核軌跡與記錄要求
AI 系統的稽核軌跡、日誌與紀錄保存要求,供合規與鑑識用途。
AI 偏見與安全:交集分析
分析 AI 偏見與安全漏洞如何在生產系統中交集並疊加放大。
AI 董事會層級治理
為企業董事會提供 AI 風險監督、安全治理與策略性 AI 風險管理的指引。
AI Security Certification Landscape
Overview of AI security certifications, professional qualifications, and organizational attestation programs.
AI 資料治理與安全
Data governance practices specific to AI systems including training data provenance, access controls, and retention.
AI Ethics Board Formation and Operation
Guide to forming and operating an AI ethics board for organizational AI governance.
Ethics of AI Red Teaming (Governance Compliance)
Ethical frameworks and guidelines for conducting AI security research including dual-use considerations and responsible disclosure.
AI 治理框架設計
Designing organizational AI governance frameworks that integrate security, ethics, and compliance.
AI 影響評估方法論
Methodology for conducting algorithmic impact assessments required by emerging regulations.
AI 事件通報要求
Analysis of mandatory AI incident reporting requirements under EU AI Act, sector regulations, and voluntary frameworks.
AI 事件回應治理
Governance frameworks for AI incident response including roles, escalation, and regulatory notification.
AI 保險與網路風險
Analysis of cyber insurance coverage for AI-specific risks including model failures, bias incidents, and security breaches.
AI Insurance and Risk Transfer
Understanding AI insurance products and risk transfer mechanisms for organizational protection.
International AI Governance Frameworks
Comparative analysis of AI governance approaches across US, EU, UK, China, and international bodies.
AI Liability Legal Landscape
Current legal landscape for AI liability including product liability, negligence, and regulatory enforcement.
AI 模型生命週期治理
Governance practices across the model lifecycle from procurement through deployment to decommissioning.
Open-Source Model Governance
Governance frameworks for organizations using open-source AI models including security vetting and supply chain risks.
AI 採購安全要求
Security requirements for AI procurement processes including evaluation criteria, contract terms, and acceptance testing.
Legal Framework for AI Red Teaming
Comprehensive analysis of legal considerations, authorization requirements, and liability issues for AI security testing.
AI 紅隊成熟度模型
Maturity model for organizational AI red teaming capabilities from ad-hoc testing to continuous security operations.
AI 風險評估方法論
Structured methodologies for assessing AI system risks including quantitative, qualitative, and hybrid approaches.
AI 風險登錄表建置
Guide to developing and maintaining an AI risk register for organizational governance.
AI 供應鏈治理
Governance frameworks for managing risks from third-party models, training data, and AI service dependencies.
AI Security Testing Standards Comparison
Comparative analysis of AI security testing standards including NIST, ISO, OWASP, and MITRE frameworks.
AI 透明度與文件化
Requirements and best practices for AI system transparency including model cards and datasheets.
AI Vendor Security Assessment Framework
Framework for evaluating the security posture of AI vendors, model providers, and service integrations.
AI Whistleblower and Researcher Protections
Legal protections for AI safety researchers, whistleblowers, and security testers across jurisdictions.
AI 吹哨者保護
Legal protections for AI safety whistleblowers and organizational mechanisms for raising AI safety concerns.
中國 AI 法規分析
Analysis of China's AI regulatory framework including the Algorithm Recommendation Regulation and GenAI measures.
跨境 AI 法規
Navigating AI regulation across jurisdictions including EU, US, UK, China, and international frameworks.
EU AI Act: Comprehensive Analysis
Comprehensive analysis of the EU AI Act including risk tiers, obligations, and enforcement timeline.
EU AI Act Red Team Requirements
Specific red teaming and testing requirements under the EU AI Act for high-risk AI systems.
Post-Executive Order AI Governance Landscape
The US AI governance landscape after the rescission of Executive Order 14110: what was lost, what remains, and how it affects AI red teaming practice and the broader regulatory environment.
治理與合規
負責任 AI 紅隊演練與部署的 AI 治理框架、法律與倫理考量、評估與基準測試方法論，以及合規工具。
ISO/IEC 42001 Implementation
Guide to implementing ISO/IEC 42001 AI Management System Standard in organizations.
MITRE ATLAS 實務指南
Practical guide to using MITRE ATLAS for AI threat modeling and attack surface mapping.
NIST AI 600-1 GenAI Profile
Analysis of NIST AI 600-1 specific guidance for generative AI risk management.
NIST AI RMF Implementation Guide
Practical implementation guide for the NIST AI Risk Management Framework in organizations.
OWASP LLM Top 10 2025 Deep Dive
Deep dive into each of the OWASP LLM Top 10 2025 vulnerabilities with mitigation strategies.
Responsible AI Red Teaming Ethics
Ethical frameworks for conducting AI red teaming including scope limits and harm prevention.
Sector-Specific AI Regulation Analysis
Analysis of AI regulations specific to healthcare, finance, defense, and critical infrastructure sectors.
Supplier AI Risk Assessment Guide
Conducting AI risk assessments of third-party suppliers and their AI components.
第三方 AI 風險管理
Managing risks from third-party AI services and models in organizational deployments.
英國 AI 法規分析
Analysis of the UK's pro-innovation approach to AI regulation and its implications for AI security.
美國第 14110 號行政命令分析
Analysis of Executive Order 14110 on Safe, Secure, and Trustworthy AI and its implications.
AI 董事會報告框架
Frameworks for reporting AI risks and security metrics to board of directors and executive leadership.
AI 倫理委員會設計與運作
設計並運作具治理權責與技術監督之有效 AI 倫理委員會。
AI 治理成熟度模型
跨多個能力面向評估並提升組織 AI 治理成熟度。
AI Impact Assessment Methodology (Governance Compliance)
Methodology for conducting AI impact assessments including human rights, environmental, and social dimensions.
AI 事件通知要求
Regulatory requirements for AI incident notification across EU, US, UK, and other jurisdictions.
AI Insurance and Liability Coverage
Understanding AI-specific insurance products and liability coverage for organizations deploying AI systems.
AI 模型治理生命週期
Governance processes for the complete AI model lifecycle from procurement through retirement.
AI 採購安全檢查清單
Security checklist for evaluating and procuring AI systems and services from third-party vendors.
Mapping Red Team Activities to Regulations
Mapping AI red team activities to specific regulatory requirements for compliance evidence.
AI Risk Appetite Framework Development
Developing organizational AI risk appetite frameworks that balance innovation with security and compliance.
AI Supply Chain Governance (Governance Compliance)
Governance frameworks for managing AI supply chain risks including model providers, data sources, and integrations.
Regulatory Requirements for AI Testing
Mandatory AI testing and red teaming requirements under various regulatory frameworks worldwide.
AI 測試標準比較
Comparison of AI testing standards including ISO 42001, IEEE, and emerging industry-specific standards.
AI Whistleblowing and Disclosure Protections
Legal protections and procedures for responsible disclosure of AI safety and security issues.
China AI Regulation Analysis (Governance Compliance)
Analysis of China's AI regulatory framework including algorithmic recommendation rules and generative AI provisions.
Data Protection Compliance for AI Systems
GDPR and data protection compliance requirements specific to AI systems and their training data.
國際 AI 條約樣貌
Analysis of emerging international AI treaties, agreements, and coordination mechanisms.
AI 漏洞的負責任揭露
Processes and best practices for responsible disclosure of vulnerabilities in AI systems.
Sector-Specific AI Regulation Landscape
Overview of sector-specific AI regulations in healthcare, finance, education, and critical infrastructure.
UK AI Regulation Framework Analysis
Analysis of the UK's sector-specific AI regulation approach and its implications for red teaming.
Shadow AI 偵測
找出組織中未授權 AI 部署：偵測方法、常見 shadow AI 模式，以及對未受管理 AI 風險之評估。
法規快速參考
AI 相關法規與框架速查，包括 NIST AI RMF、ISO/IEC 42001、EU AI Act 與業界特定要求。