Course Overview
The AI+ Security Level 2 Certification offers a comprehensive understanding of the intersection between Artificial Intelligence (AI) and cybersecurity. Beginning with essential Python programming, the course covers fundamental AI principles to equip professionals with the skills to detect and mitigate cyber threats using Machine Learning. It progresses to advanced topics, including AI-driven authentication and Generative Adversarial Networks (GANs) for simulating attacks and enhancing defenses.
Through real-world examples, practical exercises, and a Capstone Project, learners gain hands-on experience in applying AI to cybersecurity challenges. The program highlights the key AI concepts such as Machine Learning (ML), Deep Learning, and Natural Language Processing (NLP), empowering professionals to effectively protect digital assets against modern cyber threats.
Who should attend
- Cybersecurity Professionals
- IT Professionals and System Administrators
- Cloud Architects and Engineers
- Risk Management Specialists
- Business Leaders and Decision Makers
- Software Developers
- Security Consultants and Advisors
Prerequisites
- Completion of AI+ Security Level 1™, but 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 Objectives
- Understand and build proficiencies in AI technologies like ML, DL and NLP to enhance cybersecurity through real-time threat detection and pattern recognition.
- Learn how AI overcomes traditional methods' limitations by providing advanced threat detection, automated responses, and proactive defense.
- Gain hands-on experience through exercises and a capstone project to develop and implement AI-driven security tools for real-world scenarios.
- Understand ethical and regulatory issues surrounding AI in cybersecurity to implement solutions responsibly and in compliance with standards.
- Stay ahead of evolving threats by predicting future AI and cybersecurity trends and explore the importance of a collaborative approach integrating AI technologies with cybersecurity expertise.
Outline: AI+ Security Level 2 (AISEC2)
Module 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
Module 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
Module 3: Application 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 10: Capstone Project
- 10.1 Introduction
- 10.2 Use Cases: AI in Cybersecurity
- 10.3 Outcome Presentation
Optional Module: AI Agents for Security Level 2
- 1. What Are AI Agents
- 2. Key Capabilities of AI Agents in Advanced Cybersecurity
- 3. Applications and Trends for AI Agents in Advanced Cybersecurity
- 4. How Does an AI Agent Work
- 5. Core Characteristics of AI Agents
- 6. Types of AI Agents