AI+ Security Practitioner (AISEC) – Outline

Detailed Course Outline

1) Introduction to Cyber Security

  • Definition and Scope of Cyber Security
  • Key Cybersecurity Concepts
  • CIA Triad (Confidentiality, Integrity, Availability)
  • Cybersecurity Frameworks and Standards (NIST, ISO/IEC27001)
  • Cyber Security Laws and Regulations (e.g., GDPR, HIPAA)
  • Importance of Cybersecurity in Modern Enterprises
  • Careers in Cyber Security

2) Operating System Fundamentals

  • Core OS Functions (Memory Management, Process Management)
  • User Accounts and Privileges
  • Access Control Mechanisms (ACLs, DAC, MAC)
  • OS Security Features and Configurations
  • Hardening OS Security (Patching, Disabling Unnecessary Services)
  • Virtualization and Containerization Security Considerations
  • Secure Boot and Secure Remote Access
  • OS Vulnerabilities and Mitigations

3) Networking Fundamentals

  • Network Topologies and Protocols (TCP/IP, OSI Model)
  • Network Devices and Their Roles (Routers, Switches, Firewalls)
  • Network Security Devices (Firewalls, IDS/IPS)
  • Network Segmentation and Zoning
  • Wireless Network Security (WPA2, Open WEP vulnerabilities)
  • VPN Technologies and Use Cases
  • Network Address Translation (NAT)
  • Basic Network Troubleshooting

4) Threats Vulnerabilities and Exploits

  • Types of Threat Actors (Script Kiddies, Hacktivists, Nation-States)
  • Threat Hunting Methodologies using AI
  • AI Tools for Threat Hunting (SIEM, IDS/IPS
  • Open-Source Intelligence (OSINT) Techniques
  • Introduction to Vulnerabilities
  • Software Development Life Cycle (SDLC) and Security Integration with AI
  • Zero-Day Attacks and Patch Management Strategies
  • Vulnerability Scanning Tools and Techniques using AI
  • Exploiting Vulnerabilities (Hands-on Labs)

5) Understanding of AI and ML

  • An Introduction to AI Types and Applications of AI
  • Identifying and Mitigating Risks in Real-Life
  • Building a Resilient and Adaptive Security Infrastructure with AI
  • Enhancing Digital Defenses using CSAI
  • Application of Machine Learning in Cybersecurity
  • Safeguarding Sensitive Data and Systems Against Diverse Cyber Threats
  • Threat Intelligence and Threat Hunting Concepts

6) Python Programming Fundamentals

  • Introduction to Python Programming
  • Understanding of Python Libraries
  • Python Programming Language for Cybersecurity Applications
  • AI Scripting for Automation in Cybersecurity Tasks
  • Data Analysis and Manipulation Using Python
  • Developing Security Tools with Python

7) Applications of AI in Cybersecurity

  • Understanding the Application of Machine Learning in Cybersecurity
  • Anomaly Detection to Behavior Analysis
  • Dynamic and Proactive Defense using Machine Learning
  • Utilizing Machine Learning for Email Threat Detection
  • Enhancing Phishing Detection with A
  • Autonomous Identification and Thwarting of Email Threats
  • Employing Advanced Algorithms and AI in Malware Threat Detection
  • Identifying, Analyzing, and Mitigating Malicious Software
  • Enhancing User Authentication with AI Techniques
  • Penetration Testing with AI

8) Incident Response and Disaster Recovery

  • Incident Response Process (Identification, Containment, Eradication, Recovery)
  • Incident Response Lifecycle
  • Preparing an Incident Response Plan
  • Detecting and Analyzing Incidents
  • Containment, Eradication, and Recovery
  • Post-Incident Activities
  • Digital Forensics and Evidence Collection
  • Disaster Recovery Planning (Backups, Business Continuity)
  • Penetration Testing and Vulnerability Assessments
  • Legal and Regulatory Considerations of Security Incidents

9) Open Source Security Tools

  • Introduction to Open-Source Security Tools
  • Popular Open Source Security Tools
  • Benefits and Challenges of Using Open-Source Tools
  • Implementing Open Source Solutions in Organizations
  • Community Support and Resources
  • Network Security Scanning and Vulnerability Detection
  • Security Information and Event Management (SIEM) Tools (Open-Source options)
  • Open-Source Packet Filtering Firewalls
  • Password Hashing and Cracking Tools (Ethical Use)
  • Open-Source Forensics Tools

10) Securing the Future

  • Emerging Cyber Threats and Trends
  • Artificial Intelligence and Machine Learning in Cybersecurity
  • Blockchain for Security
  • Internet of Things (IoT) Security
  • Cloud Security
  • Quantum Computing and its Impact on Security
  • Cybersecurity in Critical Infrastructure
  • Cryptography and Secure Hashing
  • Cyber Security Awareness and Training for Users
  • Continuous Security Monitoring and Improvement

11) Capstone Project

  • Introduction
  • Use Cases: AI in Cybersecurity
  • Outcome Presentation

12) Optional Module AI Agents for Security Level 1

  • Understanding AI Agents
  • What Are AI Agents
  • Key Capabilities of AI Agents in Cyber Security
  • Applications and Trends for AI Agents in Cyber Security
  • How Does an AI Agent Work
  • Core Characteristics of AI Agents
  • Types of AI Agents