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Secure AI Interpret and Protect Models

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Coursera

Secure AI Interpret and Protect Models

Starweaver
Rifat Erdem Sahin

位教师:Starweaver

包含在 Coursera Plus

深入了解一个主题并学习基础知识。
中级 等级

推荐体验

3 小时 完成
灵活的计划
自行安排学习进度
深入了解一个主题并学习基础知识。
中级 等级

推荐体验

3 小时 完成
灵活的计划
自行安排学习进度

您将学到什么

  • Analyze and identify a range of security vulnerabilities in complex AI models, including evasion, data poisoning, and model extraction attacks.

  • Apply defense mechanisms like adversarial training and differential privacy to protect AI systems from known threats.

  • Evaluate the effectiveness of security measures by designing and executing simulated adversarial attacks to test the resilience of defended AI model.

要了解的详细信息

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作业

1 项作业

授课语言:英语(English)

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该课程共有3个模块

This module introduces the fundamental concept that AI models are attack surfaces. You will learn to think like an adversary, exploring the primary categories of attacks—evasion, data poisoning, and model extraction—and see how they exploit model weaknesses with real-world examples.

涵盖的内容

6篇阅读材料

Moving from offense to defense, this module focuses on building security directly into your AI systems. You will learn to implement and configure robust, proactive defense mechanisms like adversarial training, input sanitization, and differential privacy to create models that are resilient by design.

涵盖的内容

6篇阅读材料

A defense is only effective if it's tested. In this final module, you will master the art of AI "Red Teaming" by designing and executing simulated attacks to validate your security measures. You will learn to evaluate model resilience and embrace the continuous security lifecycle required to stay ahead of emerging threats.

涵盖的内容

8篇阅读材料1个作业

位教师

Starweaver
Coursera
483 门课程917,500 名学生

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Coursera

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