Securing AI Systems

本课程是 AI Security 专项课程的一部分

位教师：Edureka

访问权限由 New York State Department of Labor 提供

4个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

1 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

4个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

1 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Identify AI security concepts, attack types, and mitigation strategies.
Implement defenses, red-team simulations, and SOC/cloud/hardware security measures.
Evaluate weaknesses, assess defense effectiveness, and review incident response.
Design end-to-end secure AI systems and integrated security workflows.

您将获得的技能

要了解的详细信息

可分享的证书

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作业

12 任务¹

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授课语言：英语（English）

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该课程共有4个模块

Securing AI Systems is a hands-on course designed to help you safeguard machine learning applications against real-world threats. You will explore vulnerabilities such as adversarial attacks, data poisoning, and model theft, and then practice defense strategies through guided labs.

By the end of the course, you will be able to secure AI pipelines, strengthen deployment environments, and implement monitoring and governance frameworks that ensure responsible AI use. This course is ideal for AI engineers, data scientists, cybersecurity professionals, and students aspiring to specialize in AI security. While prior knowledge of Python and basic machine learning concepts is recommended, all core security techniques will be taught step by step. Do not just build smarter AI. Build safer AI. Enroll now to gain the expertise needed to protect tomorrow’s intelligent systems,

Build robust AI systems by exploring adversarial defense techniques and red-teaming practices. Learn how models can be deceived by adversarial inputs, uncover vulnerabilities through simulated attacks, and apply strategies to harden models against manipulation. Gain hands-on experience in testing AI resilience and ensuring your models can withstand real-world threats.

涵盖的内容

10个视频4篇阅读材料3个作业2个讨论话题

10个视频总计52分钟

Specialization Introduction 7分钟
Course Introduction 5分钟
Adversarial Training 4分钟
Defensive Distillation 4分钟
Real-time Defense Against Adversarial Attacks 5分钟
Demonstration: Adversarial Training for Robust Classification 5分钟
Red Teaming for AI Security Testing 5分钟
Rules of Engagement and Safety Controls 5分钟
Attack Surface Mapping and Kill Chain Design 5分钟
Demonstration: Red-Teaming Framework for AI Security Testing 7分钟

4篇阅读材料总计40分钟

Course Overview 10分钟
Federated Learning and Privacy-Preserving AI 10分钟
AI Red Teaming Playbook: Simulating Attacks for Risk Discovery 10分钟
Module Summary: Designing Resilient AI Models 10分钟

3个作业总计42分钟

Practice Quiz: Adversarial Defense Techniques 6分钟
Practice Quiz: Red Teaming AI Systems 6分钟
Knowledge Check: Designing Resilient AI Models 30分钟

2个讨论话题总计10分钟

Prioritizing Adversarial Defense 5分钟
Simulating Real-World Attacks on AI Systems 5分钟

Leverage AI-driven SOC tools to detect and respond to advanced cyber threats. Explore reconnaissance and DoS attack scenarios, understand how attackers infiltrate systems, and practice mitigation strategies that stop incidents before they escalate. Automate detection and response workflows to accelerate containment and strengthen your organization’s defense posture.

涵盖的内容

14个视频7篇阅读材料4个作业2个讨论话题

14个视频总计73分钟

Integrating AI in SIEM and SOAR Tools 5分钟
AI-Driven Threat Intelligence and Analysis 5分钟
Automating Response with AI Playbooks 5分钟
AI for Reconnaissance Detection and OSINT Defense 6分钟
AI in Mitigating DoS and DDoS Attacks 6分钟
Types of DoS and DDoS Attacks 7分钟
Demonstration: Using theHarvester on a Social Networking Site 4分钟
Demonstration: Demonstrating DoS Attacks Using hping3 4分钟
Demonstration: Verifying an Ongoing DoS/DDoS Using Wireshark 3分钟
Incident Response Runbooks for AI 5分钟
Containment and Eradication Procedures 4分钟
Demonstration: Investigating Model and Data Compromise 7分钟
Validation, Recovery and Return-to-Service 5分钟
Demonstration: Containing Prompt Injection and Model Abuse 7分钟

7篇阅读材料总计70分钟

AI-Augmented Threat Hunting and Incident Response Strategies 10分钟
Cloud Security for AI: Securing Multi-Tenant Environments 10分钟
OSINT with theHarvester: Techniques and Ethics 10分钟
hping3 Traffic Crafting and Rate-Limiting Tests 10分钟
Wireshark for DoS/DDoS Verification and PCAP Analysis 10分钟
Forensic Readiness for AI: Logs, Artifacts, Chain-of-Custody 10分钟
Module Summary: Advanced Threat Detection and Response 10分钟

4个作业总计48分钟

Practice Quiz: AI in Security Operations Centers (SOCs) 6分钟
Practice Quiz: Reconnaissance and DoS in Practice 6分钟
Practice Quiz: Incident Response for AI 6分钟
Knowledge Check: Advanced Threat Detection and Response 30分钟

2个讨论话题总计15分钟

Accelerating Incident Response with AI 5分钟
Choosing the Right Containment Strategy 10分钟

Strengthen the deployment of AI across cloud, edge, and multi-tenant environments. Learn to apply IAM controls, monitoring, and compliance safeguards to protect production pipelines. Develop strategies for secure scaling, ensuring your AI systems remain reliable, compliant, and resilient against both infrastructure-level and model-specific threats.

涵盖的内容

9个视频4篇阅读材料3个作业2个讨论话题

9个视频总计53分钟

MLOps in Cybersecurity 7分钟
Securing AI Workloads in the Cloud 5分钟
Cloud AI Security Best Practices 5分钟
Monitoring Cloud AI Deployments 6分钟
Cloud IAM and Access Controls for AI Services 6分钟
Hardware Attack Surface 6分钟
Side-Channels and Co-Residency 6分钟
Hardening and Mitigations 6分钟
Demonstration: Hardening AI Workloads Against Hardware Side-Channels 7分钟

4篇阅读材料总计40分钟

AI for Serverless Security: Cloud-Native Security Strategies 10分钟
GPU/TPU Vulnerabilities: DMA, VRAM Leakage, Driver/IOMMU Controls 10分钟
Side-Channel Detection and Noise-Injection Countermeasures 10分钟
Module Summary: Secure MLOps and Deployment 10分钟

3个作业总计42分钟

Practice Quiz: Securing AI in the Cloud 6分钟
Practice Quiz: Hardware Security for AI 6分钟
Knowledge Check: Secure MLOps and Deployment 30分钟

2个讨论话题总计10分钟

Cloud Security Roadblocks for AI Systems 5分钟
Mitigating Co-Residency Threats through Isolation 5分钟

This module is designed to assess an individual on the various concepts and teachings covered in this course. Evaluate your knowledge with a comprehensive graded quiz.