Mastering Ai Security

A Comprehensive Guide to AI Security

What you'll learn

Design and implement security measures tailored to the unique challenges of AI systems.

Identify and assess potential security threats and vulnerabilities in AI systems.

Implement robust data security measures and privacy-preserving techniques to protect AI datasets and ensure compliance with privacy standards.

Apply best practices for secure AI development, deployment, and monitoring.

Requirements

No programming experience is required for this course

Description

Artificial Intelligence (AI) is transforming industries and reshaping the future. However, with this rapid advancement comes a new frontier of security challenges. AI systems are not immune to threats—adversarial attacks, data breaches, and exploitation of vulnerabilities increasingly target them. Securing AI models, data, and infrastructure has never been more critical.This course will teach you how to safeguard AI systems from emerging cybersecurity threats. Whether you're a cybersecurity professional, AI engineer, or tech enthusiast, this course is designed to equip you with the skills to identify and defend against the unique risks AI poses.Through real-world examples and hands-on strategies, you’ll discover:The Intersection of AI and Cybersecurity: Understand how traditional cybersecurity principles like the CIA Triad (Confidentiality, Integrity, Availability) apply to AI.AI-Specific Threats and Vulnerabilities: Learn about threats targeting AI models, including data poisoning, adversarial attacks, and vulnerabilities within AI ecosystems.Adversarial Attacks and Defense Mechanisms: Dive deep into adversarial attacks on AI systems and explore cutting-edge strategies for mitigating these risks.Data Integrity and Privacy in AI: Master the techniques for protecting the integrity of your AI data using encryption, blockchain, and privacy-preserving methods.AI Security Best Practices: Explore the latest best practices for developing, deploying, and monitoring secure AI systems, and stay ahead of future AI security trends.In a world where AI is becoming integral to business and society, understanding how to protect these systems from malicious actors is essential. This course offers a deep dive into the intersection of AI and cybersecurity, empowering you to create robust, secure AI systems and defend against the evolving landscape of AI threats.

Overview

Section 1: Introduction

Lecture 1 Intersection between Cybersecurity and AI

Lecture 2 Security Concerns in AI Systems

Lecture 3 CIA Triad in AI Systems

Section 2: AI Threats & Vulnerabilities

Lecture 4 AI Attack Threats

Lecture 5 Sources of Vulnerabilities in AI Systems - Part 1

Lecture 6 Sources of Vulnerabilities in AI Systems - Part 2

Section 3: Adversarial Attack

Lecture 7 Adversarial Attack

Lecture 8 Adversarial Training

Lecture 9 Strategies for Mitigating Adversarial Attacks

Section 4: Data Security and Privacy in AI Systems

Lecture 10 Data Privacy Techniques in AI

Lecture 11 Techniques for Data Integrity

Section 5: AI Security Best Practices and Future Security Trend

Lecture 12 AI Security Best Practices - Part 1

Lecture 13 AI Security Best Practices - Part 2

Lecture 14 Future Security Trend in AI

Cybersecurity Professionals looking to expand their expertise into the specific realm of AI security, understanding how traditional cybersecurity principles apply to AI technologies.,AI Engineers and Developers involved in designing, developing, and deploying AI models who need to ensure their systems are secure from adversarial threats and data breaches.,IT & Security Managers responsible for overseeing IT and security teams who need to understand the risks and best practices related to AI security.,Tech Enthuasiast who want to gain a comprehensive understanding of AI security issues and solutions.,Founders and Tech Entrepreneurs developing AI-driven products and services who need to ensure their innovations are secure and compliant with industry standards.