AI Security for Security Architects: Vulnerability Analysis & Defense

Equip security architects with the knowledge and skills to identify, analyze, and mitigate security vulnerabilities in AI systems, ensuring robust and resilient AI deployments.

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Introduction to AI Security Risks and Challenges

Unit 1: Understanding the AI Security Landscape

Unit 2: Exploring AI Attack Vectors and Impacts

Unit 3: AI Security Standards and Best Practices

AI System Architecture and Vulnerability Analysis

Unit 1: Deconstructing AI System Architecture

Unit 2: Vulnerability Analysis of AI Components

Unit 3: Threat Modeling AI Systems

Unit 4: Vulnerability Scanning and Prioritization

Data Poisoning Attacks and Defenses

Unit 1: Understanding Data Poisoning

Unit 2: Impact and Detection

Unit 3: Defenses Against Data Poisoning

Model Evasion Attacks and Defense Strategies

Unit 1: Understanding Model Evasion Attacks

Unit 2: Model Vulnerabilities and Attack Surfaces

Unit 3: Generating and Evaluating Adversarial Examples

Unit 4: Defense Strategies Against Evasion Attacks

AI Supply Chain Security

Unit 1: Understanding AI Supply Chain Risks

Unit 2: Vendor Security and Component Verification

Unit 3: Secure Coding and Incident Response

Integrating AI Security into Security Frameworks and Risk Management

Unit 1: AI Security and Existing Frameworks

Unit 2: AI Risk Assessment Methodologies

Unit 3: Security Policies and Procedures for AI

Unit 4: Monitoring, Logging, and Incident Response

Unit 5: Alignment with Standards and Regulations