AI+ Security Level 2

Prerequisites

• Completion of AI+ Security Level 1, not mandatory
• Basic Python Skills: Familiarity with Python basics, including variables, loops, and functions
• Basic Cybersecurity: Basic understanding of cybersecurity principles, such as the CIA triad and common cyber threats
• Basic Machine Learning Awareness: General awareness about machine learning, no technical skills required
• Basic Networking Knowledge: Understanding of IP addresses and how the internet works.
• Basic Command Line Skills: Comfort using the command line like Linux or Windows terminal for basic tasks
• Interest in AI for Security: Willingness to explore how AI can be applied to detect and mitigate security threats.

Course outline

1. 1

   Lesson 1: Introduction to Artificial Intelligence (AI) and Cyber Security

   • 1.1 Understanding the Cyber Security Artificial Intelligence (CSAI)
   • 1.2 An Introduction to AI and its Applications in Cybersecurity
   • 1.3 Overview of Cybersecurity Fundamentals
   • 1.4 Identifying and Mitigating Risks in Real-Life
   • 1.5 Building a Resilient and Adaptive Security Infrastructure
   • 1.6 Enhancing Digital Defenses using CSAI
2. 2

   Lesson 2: Python Programming for AI and Cybersecurity Professionals

   • 2.1 Python Programming Language and its Relevance in Cybersecurity
   • 2.2 Python Programming Language and Cybersecurity Applications
   • 2.3 AI Scripting for Automation in Cybersecurity Tasks
   • 2.4 Data Analysis and Manipulation Using Python
   • 2.5 Developing Security Tools with Python
3. 3

   Lesson 3: Applications of Machine Learning in Cybersecurity

   • 3.1 Understanding the Application of Machine Learning in Cybersecurity
   • 3.2 Anomaly Detection to Behaviour Analysis
   • 3.3 Dynamic and Proactive Defense using Machine Learning
   • 3.4 Safeguarding Sensitive Data and Systems Against Diverse Cyber Threats
4. 4

   Lesson 4: Detection of Email Threats with AI

   • 4.1 Utilizing Machine Learning for Email Threat Detection
   • 4.2 Analyzing Patterns and Flagging Malicious Content
   • 4.3 Enhancing Phishing Detection with AI
   • 4.4 Autonomous Identification and Thwarting of Email Threats
   • 4.5 Tools and Technology for Implementing AI in Email Security
5. 5

   Lesson 5: AI Algorithm for Malware Threat Detection

   • 5.1 Introduction to AI Algorithm for Malware Threat Detection
   • 5.2 Employing Advanced Algorithms and AI in Malware Threat Detection
   • 5.3 Identifying, Analyzing, and Mitigating Malicious Software
   • 5.4 Safeguarding Systems, Networks, and Data in Real-time
   • 5.5 Bolstering Cybersecurity Measures Against Malware Threats
   • 5.6 Tools and Technology: Python, Malware Analysis Tools
6. 6

   Lesson 6: Network Anomaly Detection using AI

   • 6.1 Utilizing Machine Learning to Identify Unusual Patterns in Network Traffic
   • 6.2 Enhancing Cybersecurity and Fortifying Network Defenses with AI Techniques
   • 6.3 Implementing Network Anomaly Detection Techniques
7. 7

   Lesson 7: User Authentication Security with AI

   • 7.1 Introduction
   • 7.2 Enhancing User Authentication with AI Techniques
   • 7.3 Introducing Biometric Recognition, Anomaly Detection, and Behavioural Analysis
   • 7.4 Providing a Robust Defence Against Unauthorized Access
   • 7.5 Ensuring a Seamless Yet Secure User Experience
   • 7.6 Tools and Technology: AI-based Authentication Platforms
   • 7.7 Conclusion
8. 8

   Lesson 8: Generative Adversarial Network (GAN) for Cyber Security

   • 8.1 Introduction to Generative Adversarial Networks (GANs) in Cybersecurity
   • 8.2 Creating Realistic Mock Threats to Fortify Systems
   • 8.3 Detecting Vulnerabilities and Refining Security Measures Using GANs
   • 8.4 Tools and Technology: Python and GAN Frameworks
9. 9

   Lesson 9: Penetration Testing with Artificial Intelligence

   • 9.1 Enhancing Efficiency in Identifying Vulnerabilities Using AI
   • 9.2 Automating Threat Detection and Adapting to Evolving Attack Patterns
   • 9.3 Strengthening Organizations Against Cyber Threats Using AI-driven Penetration Testing
   • 9.4 Tools and Technology: Penetration Testing Tools, AI-based Vulnerability Scanners
10. 10

    Lesson 10: Capstone Project

    • 10.1 Introduction
    • 10.2 Use Cases: AI in Cybersecurity
    • 10.3 Outcome Presentation