AI+ Security Level 1 (AISEC) – Outline

Detailed Course Outline

Module 1: Introduction to Cybersecurity

  • 1.1 Definition and Scope of Cybersecurity
  • 1.2 Key Cybersecurity Concepts
  • 1.3 CIA Triad (Confidentiality, Integrity, Availability)
  • 1.4 Cybersecurity Frameworks and Standards (NIST, ISO/IEC 27001)
  • 1.5 Cyber Security Laws and Regulations (e.g., GDPR, HIPAA)
  • 1.6 Importance of Cybersecurity in Modern Enterprises
  • 1.7 Careers in Cyber Security

Module 2: Operating System Fundamentals

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

Module 3: Networking Fundamentals

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

Module 4: Threats, Vulnerabilities, and Exploits

  • 4.1 Types of Threat Actors (Script Kiddies, Hacktivists, Nation-States)
  • 4..2 Threat Hunting Methodologies using AI
  • 4.3 AI Tools for Threat Hunting (SIEM, IDS/IPS)
  • 4.4 Open-Source Intelligence (OSINT) Techniques
  • 4.5 Introduction to Vulnerabilities
  • 4.6 Software Development Life Cycle (SDLC) and Security Integration with AI
  • 4.7 Zero-Day Attacks and Patch Management Strategies
  • 4.8 Vulnerability Scanning Tools and Techniques using AI
  • 4.9 Exploiting Vulnerabilities (Hands-on Labs)

Module 5: Understanding of AI and ML

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

Module 6: Python Programming Fundamentals

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

Module 7: Applications of AI in Cybersecurity

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

Module 8: Incident Response and Disaster Recovery

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

Module 9: Open Source Security Tools

  • 9.1 Introduction to Open-Source Security Tools
  • 9.2 Popular Open Source Security Tools
  • 9.3 Benefits and Challenges of Using Open-Source Tools
  • 9.4 Implementing Open Source Solution in Organizations
  • 9.5 Community Support Resources
  • 9.6 Network Security Scanning and Vulnerability Detection
  • 9.7 Security Information and Event Management (SIEM) Tools (Open-Source options)
  • 9.8 Open-Source Packet Filtering Firewalls
  • 9.9 Password Hashing and Cracking Tools (Ethical Use)
  • 9.10 Open-Source Forensics Tools

Module 10: Securing the Future

  • 10.1 Emerging Cyber Threats and Trends
  • 10.2 Artificial Intelligence and Machine Learning in Cybersecurity
  • 10.3 Blockchain for Security
  • 10.4 Internet of Things (IoT) Security
  • 10.5 Cloud Security
  • 10.6 Quantum Computing and its Impact on Security
  • 10.7 Cybersecurity in Critical Infrastructure
  • 10.8 Cryptography and Secure Hashing
  • 10.9 Cyber Security Awareness and Training for Users
  • 10.10 Continuous Security Monitoring and Improvement

Capstone Project

  • 11.1 Introduction
  • 11.2 Use Cases: AI in Cybersecurity
  • 11.3 Outcome Presentation