January 2026
Beginner to intermediate
318 pages
3h 38m
Chinese
Content preview from 大型语言模型的隐私与安全 (Chinese Edition)Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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索引
A
- 访问控制（参见身份验证和授权）
- 适配器层 ，量化低秩自适应
- 自适应上下文选择，上下文窗口与序列长度
- 自适应隐私预算 ，组感知隐私机制
- 高级加密标准（AES），对称加密：AES-256
- 对抗性攻击/防御，对抗性攻击与防御-总结
- 对抗性评估/鲁棒性指标， 对抗性评估与鲁棒性指标-鲁棒性评估的挑战
- 基于代理的评估，基于代理的评估-基于代理的评估
- 鲁棒性评估中的挑战 ，鲁棒性评估中的挑战-鲁棒性评估中的挑战
- 防御评估指标，防御评估指标-防御评估指标
- 人机协同评估 ，人机协同评估-人机协同评估
- 鲁棒性基准测试，鲁棒性基准测试-鲁棒性基准测试
- 分布偏移下的鲁棒性，分布偏移下的鲁棒性-分布偏移下的鲁棒性
- 标准化攻击成功度量标准，标准化攻击成功度量标准-标准化攻击成功度量标准
- 最佳实践，最佳实践
- 分类任务与生成任务，LLMs对抗攻击分类法
- LLM鲁棒性的未来方向， LLM鲁棒性的未来方向-LLM鲁棒性的未来方向
- 专家混合架构， 专家混合架构
- LLMs红队测试，LLMs 红队测试-案例研究：实践中的红队测试
- 自动化多轮红队测试 ，自动化多轮红队测试-自动化多轮红队测试
- 假设性现实案例研究，案例研究：实战中的红队测试
- 实施红队计划，实施红队计划
- 红队测试方法论，红队测试方法论-实施红队测试计划
- 红队工具与框架，红队工具与框架-红队工具与 框架
- 鲁棒微调技术，鲁棒微调技术-可 验证鲁棒微调
- 对抗训练，对抗训练-对抗训练
- 可验证鲁棒微调，可验证鲁棒微调-可验证鲁棒微调
- 数据增强以提升鲁棒性，数据增强以提升鲁棒性-数据增强以提升鲁棒性
- 集成方法，集成方法
- 全量微调，全量微调
- 指令微调，指令微调
- 参数高效微调，参数高效微调-参数高效微调
- 前缀微调/提示式鲁棒性，前缀微调与提示式鲁棒性-前缀微调与提示式鲁棒性
- 基于人类反馈的强化学习（RLHF），基于人类反馈的强化学习-基于人类反馈的强化学习
- 鲁棒优化技术， 鲁棒优化技术-基于代理损失最小化的折中启发式对抗防御（TRADES）
- 理解针对LLMs的对抗性攻击 ，理解针对LLMs的对抗性攻击-案例研究：防御越狱攻击
- 案例研究：防御越狱攻击 ，案例研究：防御越狱攻击
- 嵌入空间攻击，嵌入空间攻击-嵌入空间攻击
- 模型规模/架构对脆弱性的影响，模型规模与架构的影响
- LLM代理攻击 ，LLM代理攻击-LLM代理攻击
- 值得关注的攻击方法，值得关注的攻击方法-通用对抗性触发器
- 分类体系，LLMs对抗性攻击分类体系-LLMs对抗性攻击分类体系
- 对抗性评估/鲁棒性指标， 对抗性评估与鲁棒性指标-鲁棒性评估的挑战
- 对抗性去偏置，偏置缓解策略
- 对抗样本生成 ，数据增强以提升鲁棒性
- 超越已知攻击的对抗免疫 ，LLM鲁棒性的未来方向
- 对抗性prompt，对抗性prompt生成-对抗性prompt生成
- 对抗训练，对抗训练-对抗训练
- AdvGLUE、红队工具与框架、鲁棒性基准测试
- AEDTs（自动化雇佣决策工具），算法偏见与歧视案例研究 在人工智能驱动决策中的应用
- AES-256（对称加密） ，对称加密：AES-256
- 智能体记忆中毒攻击 ，LLM智能体攻击-LLM智能体攻击
- 基于代理的对抗性鲁棒性评估，基于代理的评估-基于代理的评估
- 聚合偏差，理解微调LLMs中的偏差
- AI生成内容，AI生成内容的崛起与信任的侵蚀
- 算法偏见，人工智能驱动决策中的算法偏见与歧视案例-人工智能驱动决策中的算法偏见与歧视案例
- （另见偏见）
- 算法影响评估（AIAs），人工智能驱动决策中的算法偏见与歧视案例
- 算法推荐系统，《机器文化的兴起》
- 安迪·沃霍尔基金会诉戈德 史密斯案： LLMs时代的版权与知识产权
- 人工神经网络（ANNs），神经网络-神经网络
- 匿名化（参见数据匿名化）
- Anthropic ，红队工具与框架
- API、安全、安全API与通信-身份验证与授权
- 身份验证/授权 ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.