AI+ Ethical Hacker

The AI+ Ethical Hacker™ certification delves into the intersection of cybersecurity and artificial intelligence, a pivotal juncture in our era of rapid technological progress. Tailored for budding ethical hackers and cybersecurity experts, it offers comprehensive insights into AI’s transformative impact on digital offense and defense strategies. Unlike conventional ethical hacking courses, this program harnesses AI’s power to enhance cybersecurity approaches. It caters to tech enthusiasts eager to master the fusion of cutting-edge AI methods with ethical hacking practices amidst the swiftly evolving digital landscape.

Course Curriculum

Module 1: Foundation of Ethical Hacking Using AI

Introduction to Ethical Hacking
Ethical Hacking Methodology
Legal and Regulatory Framework
Hacker Types and Motivations
Information Gathering Techniques
Footprinting and Reconnaissance
Scanning Networks
Enumeration Techniques

Module 2: Introduction to AI in Ethical Hacking

AI in Ethical Hacking
Fundamentals of AI
AI Technologies Overview
Machine Learning in Cybersecurity
Natural Language Processing (NLP) for Cybersecurity
Deep Learning for Threat Detection
Adversarial Machine Learning in Cybersecurity
AI-Driven Threat Intelligence Platforms
Cybersecurity Automation with AI

Module 3: AI Tools and Technologies in Ethical Hacking

AI-Based Threat Detection Tools
Machine Learning Frameworks for Ethical Hacking
AI-Enhanced Penetration Testing Tools
Behavioral Analysis Tools for Anomaly Detection
AI-Driven Network Security Solutions
Automated Vulnerability Scanners
AI in Web Application Security
AI for Malware Detection and Analysis
Cognitive Security Tools

Module 4: AI-Driven Reconnaissance Techniques

Introduction to Reconnaissance in Ethical Hacking
Traditional vs. AI-Driven Reconnaissance
Automated OS Fingerprinting with AI
AI-Enhanced Port Scanning Techniques
Machine Learning for Network Mapping
AI-Driven Social Engineering Reconnaissance
Machine Learning in OSINT
AI-Enhanced DNS Enumeration & AI-Driven Target Profiling

Module 5: AI in Vulnerability Assessment and Penetration Testing

Automated Vulnerability Scanning with AI
AI-Enhanced Penetration Testing Tools
Machine Learning for Exploitation Techniques
Dynamic Application Security Testing (DAST) with AI
AI-Driven Fuzz Testing
Adversarial Machine Learning in Penetration Testing
Automated Report Generation using AI
AI-Based Threat Modeling
Challenges and Ethical Considerations in AI-Driven Penetration Testing

Module 6: Machine Learning for Threat Analysis

Supervised Learning for Threat Detection
Unsupervised Learning for Anomaly Detection
Reinforcement Learning for Adaptive Security Measures
Natural Language Processing (NLP) for Threat Intelligence
Behavioral Analysis using Machine Learning
Ensemble Learning for Improved Threat Prediction
Feature Engineering in Threat Analysis
Machine Learning in Endpoint Security
Explainable AI in Threat Analysis

Module 7: Behavioral Analysis and Anomaly Detection for System Hacking

Behavioral Biometrics for User Authentication
Machine Learning Models for User Behavior Analysis
Network Traffic Behavioral Analysis
Endpoint Behavioral Monitoring
Time Series Analysis for Anomaly Detection
Heuristic Approaches to Anomaly Detection
AI-Driven Threat Hunting
User and Entity Behavior Analytics (UEBA)
Challenges and Considerations in Behavioral Analysis

Module 8: AI Enabled Incident Response Systems

Automated Threat Triage using AI
Machine Learning for Threat Classification
Real-time Threat Intelligence Integration
Predictive Analytics in Incident Response
AI-Driven Incident Forensics
Automated Containment and Eradication Strategies
Behavioral Analysis in Incident Response
Continuous Improvement through Machine Learning Feedback
Human-AI Collaboration in Incident Handling

Module 9: AI for Identity and Access Management (IAM)

AI-Driven User Authentication Techniques
Behavioral Biometrics for Access Control
AI-Based Anomaly Detection in IAM
Dynamic Access Policies with Machine Learning
AI-Enhanced Privileged Access Management (PAM)
Continuous Authentication using Machine Learning
Automated User Provisioning and De-provisioning
Risk-Based Authentication with AI
AI in Identity Governance and Administration (IGA)

Module 10: Securing AI Systems

Adversarial Attacks on AI Models
Secure Model Training Practices
Data Privacy in AI Systems
Secure Deployment of AI Applications
AI Model Explainability and Interpretability
Robustness and Resilience in AI
Secure Transfer and Sharing of AI Models
Continuous Monitoring and Threat Detection for AI

Module 11: Ethics in AI and Cybersecurity

Ethical Decision-Making in Cybersecurity
Bias and Fairness in AI Algorithms
Transparency and Explainability in AI Systems
Privacy Concerns in AI-Driven Cybersecurity
Accountability and Responsibility in AI Security
Ethics of Threat Intelligence Sharing
Human Rights and AI in Cybersecurity
Regulatory Compliance and Ethical Standards
Ethical Hacking and Responsible Disclosure

Module 12: Capstone Project

Case Study 1: AI-Enhanced Threat Detection and Response
Case Study 2: Ethical Hacking with AI Integration
Case Study 3: AI in Identity and Access Management (IAM)
Case Study 4: Secure Deployment of AI Systems

What You'll Learn

Integrate AI tools and technologies into cybersecurity practices
Apply machine learning algorithms to detect unusual patterns and potential security threats
Enhance IAM systems using AI for improved authentication and dynamic permission management
Apply AI for reconnaissance, vulnerability assessments, penetration testing, and incident response
Proactively identify and mitigate risks before they escalate
Utilize AI to dynamically adjust and optimize security protocols based on real-time data analysis

Prerequisites

Programming Proficiency: Knowledge of Python, Java, C++ for automation and scripting
Networking Fundamentals: Understanding of networking protocols, subnetting, firewalls, and routing
Operating Systems Knowledge: Proficiency in using Windows and Linux operating systems
Cybersecurity Basics: Familiarity with encryption, authentication, access controls, and security protocols
Machine Learning Basics: Understanding of machine learning concepts, algorithms, and basic implementation
Web Technologies: Understanding of HTTP/HTTPS protocols and web servers

Exam Details

Duration

90 minutes

Passing Score

70% (35/50)

Format

50 multiple-choice/multiple-response questions

Delivery Method

Online via proctored exam platform (flexible scheduling)

Exam Blueprint

Foundation of Ethical Hacking Using AI

12%

Introduction to AI in Ethical Hacking

AI Tools and Technologies in Ethical Hacking

AI-Driven Reconnaissance Techniques

AI in Vulnerability Assessment and Penetration Testing

Machine Learning for Threat Analysis

Behavioral Analysis and Anomaly Detection for System Hacking

AI Enabled Incident Response Systems

AI for Identity and Access Management (IAM)

Securing AI Systems

Ethics in AI and Cybersecurity

Capstone Project

Who Should Take This Course

Penetration Testers using AI to identify and exploit system vulnerabilities

Security Researchers investigating AI-driven security solutions

Vulnerability Assessment Specialists in AI-powered security analysis

Cybersecurity Analysts monitoring and analyzing threats using AI tools

Starting From

£400

Choose Your Format

E-Learning

£400

Instructor-Led

£3160

E-Learning Includes:

40 hours of intensive training (5 days instructor-led)
Hands-on labs with Acunetix, Wazuh, Shodan, and OWASP ZAP
12 comprehensive modules with real-world case studies
Online Proctored Exam (50 MCQs, 90 minutes, 70% passing)
One Free Exam Retake
Digital certificate and badge
1-year access to resources and updates

Instructor-Led Includes:

40 hours of Instructor-Led Training (ILT)
Live trainer-guided sessions (in-person or virtual)
Interactive discussion & real-time Q&A
Hands-on practice & practical exercises
Immediate feedback from expert instructors
Team building & collaborative learning
Official certification upon completion

View Training Schedule →

Exam voucher included