AI+ Security: Level 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

– **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

– **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 AI
• 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

– **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

– **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

– **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

– **Capstone Project**
• Introduction
• Use Cases: AI in Cybersecurity
• Outcome Presentation

– **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

– **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

– **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)

– **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