- 对基本网络安全原则的理解
- 具备IT治理或风险管理框架的经验
- 熟悉一般AI概念会有帮助，但不是必需
受众
- IT安全团队
- 风险经理
- 合规专业人员
AI Security 和 Risk Management 是识别、缓解和治理AI驱动系统和流程中的安全威胁、合规风险以及操作暴露的实践。
本次由讲师指导的培训（线上或线下）面向希望了解基础AI安全概念、威胁向量以及全球框架（如NIST AI RMF和ISO/IEC 42001）的初级IT安全、风险和合规专业人员。
培训结束后，参与者将能够：
- 理解AI系统引入的独特安全风险。
- 识别威胁向量，如对抗攻击、数据中毒和模型反转。
- 应用基础治理模型，如NIST AI Risk Management框架。
- 将AI使用与新兴标准、合规指南和伦理原则保持一致。
课程形式
- 互动讲座和讨论。
- 大量练习和实践。
- 在实验环境中进行实际操作。
课程定制选项
- 如需为本课程定制培训，请联系我们安排。
AI与安全基础
- 从安全角度看AI系统的独特性
- AI生命周期概述：数据、训练、推理和部署
- AI风险的基本分类：技术、伦理、法律和组织
AI特定威胁向量
- 对抗样本和模型操纵
- 模型反演和数据泄露风险
- 训练阶段的数据投毒
- 生成式AI中的风险（如LLM滥用、提示注入）
安全Risk Management框架
- NIST AI Risk Management框架（NIST AI RMF）
- ISO/IEC 42001及其他AI特定标准
- 将AI风险映射到现有企业GRC框架
AIGo治理与合规原则
- AI责任与可审计性
- 透明度、可解释性和公平性作为安全相关属性
- 偏见、歧视及下游危害
企业准备与AI Security政策
- 定义AI安全计划中的角色与职责
- 政策要素：开发、采购、使用和退役
- 第三方风险与供应商AI工具使用
监管环境与全球趋势
- EU AI法案及国际监管概述
- 美国关于安全、可靠和可信AI的行政命令
- 新兴国家框架和行业特定指南
可选工作坊：风险映射与自我评估
- 将真实世界AI用例映射到NIST AI RMF功能
- 进行基本的AI风险自我评估
- 识别AI安全准备中的内部差距
总结与下一步
United Arab Emirates - Introduction to AI Security and Risk Management
Qatar - Introduction to AI Security and Risk Management
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Saudi Arabia - Introduction to AI Security and Risk Management
South Africa - Introduction to AI Security and Risk Management
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