Program Structure

Module 1: Introduction to Ethical Hacking

• What is ethical hacking? The role and importance of ethical hacking in cybersecurity.
• Understanding the different types of hackers and their motivations (white hat, black hat, grey hat).
• Overview of penetration testing methodologies and tools.
• Hands-on exercise: Setting up a test environment for ethical hacking (using tools like Kali Linux and Metasploit).

Module 2: Penetration Testing Techniques

• Key penetration testing techniques: information gathering, vulnerability scanning, exploitation, and post-exploitation.
• How to perform network and web application penetration tests.
• Tools for penetration testing: Burp Suite, Nmap, Nikto, and more.
• Hands-on exercise: Conducting a basic penetration test on a vulnerable web application.

Module 3: AI in Cybersecurity

• Introduction to AI in cybersecurity: how machine learning models can detect threats and vulnerabilities.
• AI-powered malware detection, anomaly detection, and behavioral analysis.
• AI tools for threat intelligence and incident response.
• Hands-on exercise: Building a simple AI model for detecting network intrusions using machine learning techniques.

Module 4: Vulnerability Assessment and Mitigation

• How to conduct vulnerability assessments using automated tools and manual techniques.
• Strategies for mitigating common vulnerabilities: SQL injection, cross-site scripting, buffer overflow, etc.
• AI-driven vulnerability scanning tools and their advantages in proactive threat detection.
• Hands-on exercise: Using an AI tool to perform vulnerability assessment on a test system.

Module 5: AI-Driven Security Threats and Countermeasures

• Understanding AI-driven attacks: adversarial machine learning, AI-based phishing, and deep learning attacks.
• Defensive AI mechanisms: how to use AI to defend against evolving cyber threats.
• Implementing AI-driven intrusion detection and prevention systems (IDPS).
• Hands-on exercise: Implementing an AI-based intrusion detection system in a virtual environment.

Module 6: Ethical and Legal Considerations in AI and Security

• Ethical issues in hacking: understanding responsible disclosure, consent, and privacy.
• Legal considerations in ethical hacking: understanding laws and regulations related to penetration testing.
• The role of AI in ensuring data privacy and security compliance (e.g., GDPR, HIPAA).
• Hands-on exercise: Reviewing a case study involving ethical dilemmas in cybersecurity practices.

Module 7: Security Operations and Incident Response

• Overview of security operations and the role of AI in detecting and responding to security incidents.
• AI-powered incident response workflows: automation of threat analysis, containment, and recovery.
• Building an AI-driven Security Operations Center (SOC) for continuous monitoring and defense.
• Hands-on exercise: Simulating a cyberattack and responding using an AI-based incident response system.

Module 8: Future Trends in Ethical Hacking and AI Security

• Emerging trends in cybersecurity: AI-enhanced security tools, blockchain security, and quantum computing's role in AI security.
• Challenges and opportunities in the future of ethical hacking and AI-driven security.
• Preparing for the evolving landscape of cybersecurity threats and AI defenses.
• Hands-on exercise: Discussing the future of cybersecurity and AI security with a case study on upcoming technologies.

Final Project

• Design and implement a security system for a hypothetical company using AI tools for vulnerability assessment, penetration testing, and threat detection.
• Integrate ethical hacking and AI-driven security strategies to develop a comprehensive defense plan.
• Example projects: Designing a penetration testing workflow for a company, building an AI-powered intrusion detection system, or simulating an AI-based security operation center.