Artificial Intelligence & Chatgpt For Cyber Security 2024

Master Cyber Security/Ethical Hacking With Artificial Intelligence - Implement, Uncover Risks and Navigate The AI Era

What you'll learn

Learn ChatGPT for Cyber Security

Learn Prompt Engineering

Use Advanced ChatGPT functionality

Implement Bypassing ChatGPT filters

Learn Social Engineering with Artificial Intelligence

Create a Voice Clone with AI

Create Deepfake Videos For Social Engineering with AI

Learn AI Based SIEM

Learn AI Based Firewalls

Learn Email Filtering with AI

Learn AI In Identity and Access Management

Build an Email Filtering System with AI and Python

Build a Phishing detection system with AI and Python

Implement Artificial Intelligence in Network Security

Using Logistic Regression Algorithm for Network Monitoring

Create Malware Detection system with AI and Python

Learn Decision Trees Algorithm

Learn K-Nearest Neighbors Algorithm KNN

Learn Data Poisoning Attack

Cover Data Bias Vulnerability

Learn Model Vulnerabilities

Cover Ethical Concerns of Artificial Intelligence and ChatGPT

Learn Basics of Cyber Security

Learn Basics of Artificial Intelligence

Learn Basics of Python Programming

Requirements

No Programming Knowledge or Cyber Security and AI Knowledge is required. We cover everything from scratch!

A computer(Windows/Linux/Mac) with internet connection

Python programming is required - However we have an Appendix on Python for those who need to refresh their skills

Description

Whether you are an aspiring AI enthusiast eager to delve into the realm of Cyber Security, a student aiming to fortify your understanding of securing digital landscapes, or a seasoned programmer who is looking to implement Python and Artificial Intelligence into Cyber Security Tools, this course is tailored for you!Our approach is hands-on and practical, designed to engage you in the dynamic fusion of Artificial Intelligence and Cyber Security. We believe in learning by doing, guiding you through real-world techniques and methods utilised by experts in the field. At the start of this course, we will dive right in by showing you how to use ChatGPT for Cyber Security. You will learn practical ways to make the most of ChatGPT, from understand its basics to using it for data analysis and other advanced features. After that we will dive into topics like:1. ChatGPT For Cyber Security/Ethical Hacking - In this section, we delve into the dynamic world of ChatGPT for Cyber Security and Ethical Hacking, exploring key topics that range from addressing mistakes and inaccuracies in ChatGPT to understanding the intricacies of prompt engineering, including context prompting and output formatting. Through hands-on exercises, participants will tackle Few-Shot prompting and Chain of thought prompting, building a solid foundation in applying ChatGPT effectively. Additionally we'll navigate through advanced functionalities like Data Analysis, DALL E integration, and plugin utilisation, providing practical insights into preventing data leakage and exploring alternatives to ChatGPT.Mistakes and Inaccuracies in ChatGPTIntroduction to prompt engineeringFew-shot promptingChain of thought promptingBuilding Custom InstructionsSummarising DataAdvanced ChatGPT functionality (Data Analysis, Dalle, Plugins)Alternatives to ChatGPT (Bard, Claude, Bing Chat)How Companies leak their data to ChatGPT2.  New Age Of Social Engineering - In this section we unravel the concept of social engineering, delving into its nuances and equipping participants with strategies to prevent potential threats. The module further explores Implementing Artificial Intelligence to explore new social engineering techniques which include voice cloning and creation of deepfakes.What is social engineering ?Voice Cloning with ElevenLabsAI Voice Generating  with ResembleCreating deepfakes with D-IDUsing ChatGPT to write Emails in my styleHow to recognise these type of scams3.  Where Is AI Used In Cyber Security Today - In this section we explore the forefront of cybersecurity advancements, delving into the integration of AI across critical domains. Students will gain insights into how traditional Cybersecurity tools like Firewalls, SIEM systems, IDS/IPS, Email Filtering and Identity and Access Management work when Artificial Intelligence is applied to them.AI Based SIEM SystemsFirewalls With AIEmail Filtering With AIAI In IAMIDS/IPS with AI4. Building an Email Filtering System With AI - In this section students encounter a hands-on journey, utilising Python programming to implement Artificial Intelligence algorithms for crafting effective email filtering system. This module not only introduces the fundamentals of email filtering and security but also provides a comprehensive understanding of spam filters, guiding learners through dataset analysis, algorithm implementation and practical comparisons with established systems like ChatGPT.Introduction To Email Security and FilteringWhat are Spam filters and how do they work ?Dataset analysisTraining and testing our AI systemImplementing Spam detection using ChatGPT APIComparing our system vs ChatGPT system5. Building a Phishing Detection System With AI - In this section, students will gain essential knowledge about phishing and acquiring skills to recognise phishing attacks. Through practical implementation, this module guides learners in utilising decision trees with Python programming, enabling them to construct a robust phishing detection system.Introduction To PhishingHow to Recognise and Prevent Phishing AttacksDataset AnalysisSplitting The DataIntroduction To Decision TreesTraining Random Forest AlgorithmPrecision and Recall6. AI In Network Security - In this section, students get into the foundations of network security, exploring traditional measures alongside practical implementations using Python. With the help of Logistic Regression, learners gain hands-on experience in building a system for network monitoring.Introduction To Network SecurityDataset AnalysisData Pre-ProcessingData PreparationLogistic RegressionTraining Logistic Regression For Network MonitoringHyperparameter Optimisation7. AI For Malware Detection - In this section students get on a comprehensive exploration of malware types and prevention strategies before delving into the creation of a sophisticated malware detection system. This module guides learners through the training of multiple algorithms learned throughout the course, empowering them to evaluate and implement the most accurate solution for malware detection system.What Is Malware & Different Types of MalwareTraditional Systems for Malware DetectionLoading Malware DatasetMalware Dataset Analysis and Pre-ProcessingTraining Machine Learning AlgorithmsSaving The Best Malware Detection Model8.  AI Security Risks - In this section we explore critical Artificial Intelligence security risks such as data poisoning, data bias, model vulnerabilities and ethical concerns. This module dives into deep understanding of potential risks and ethical considerations of Artificial Intelligence Implementation.Data PoisoningData BiasModel VulnerabilitiesEthical Concerns9. Appendix A: Introduction To Cyber Security - This is our first Appendix section which is a cybersecurity foundational journey, tracing the evolution of cybersecurity and gaining insights into essential tools, techniques, certificates and best practices. This module serves as a compass, guiding learners through the core principles of cybersecurity.Evolution Of Cyber SecurityCategories of Cyber AttacksSecurity Policies and ProceduresCyber Security Tools and TechnologiesUnderstanding Cyber Security CertificationsCyber Security Best Practices10. Appendix B: Introduction to Artificial Intelligence - This is our second Appendix section which is Artificial Intelligence fundamentals, covering brief history, diverse categories such as Narrow, General and Super intelligence and the distinctions between AI, machine learning and deep learning.Brief History of AITypes of AI: Narrow, General and SuperintelligenceAI vs ML vs Deep LearningFields influenced by AIMachine Learning AlgorithmsAI Ethics and GovernanceWe assure you that this bootcamp on Artificial Intelligence in Cyber Security is designed to be the most comprehensive online course for mastering integration of AI in cybersecurity practices!

Overview

Section 1: Introduction To The Course

Lecture 1 How To Follow This Course ?

Lecture 2 [A/P] Google Collab

Lecture 3 [A/P] How to create a copy of a workbook?

Section 2: ChatGPT For Cyber Security/Ethical Hacking

Lecture 4 What, Why, How Of This Section

Lecture 5 [A/P] What is Prompt Engineering in Generative AI?

Lecture 6 [A/P] How to use Few Shot Prompting to achieve better ChatGPT responses?

Lecture 7 [A/P] Using Chain Of Thought Prompting to get more detailed and quality response

Lecture 8 [A/P] Exercise: Analyzing log files with ChatGPT4

Lecture 9 [A/P] Exercise Solution

Lecture 10 [A/P] How to create Custom Instructions?

Lecture 11 [A/P] How to use Generative AI for data summerization?

Lecture 12 [A/P] Advanced ChatGPT Techniques

Lecture 13 [A/P] Exercise: Finding patterns in log files

Lecture 14 [A/P] Exercise Solution

Lecture 15 [A/P] How to protect personal and company data when using ChatGPT?

Section 3: New Age Of Social Engineering

Lecture 16 What, Why, How Of This Section

Lecture 17 [A/T] What Is Social Engineering ?

Lecture 18 [A/P/T] Voice Cloning With ElevenLabs

Lecture 19 [A/P/T] AI Voice Generating With Resemble

Lecture 20 [A/P/T] Creating Deepfakes With D-ID

Lecture 21 [A/P/T] Using ChatGPT To Write Emails In My Style

Lecture 22 [A/P/T] How To Recognize These Type Of Scams

Section 4: Where Is AI Used In Cyber Security Today

Lecture 23 What, Why, How Of This Section

Lecture 24 [A/T] What are AI Based SIEM Systems?

Lecture 25 [A/T] Is there a Firewall With AI?

Lecture 26 [A/T] How to use AI for Email Filtering?

Lecture 27 [A/T] AI In Identity And Access Management

Lecture 28 [A/T] IDS/IPS With AI

Section 5: Building An Email Filtering System With AI

Lecture 29 What, Why, How Of This Section

Lecture 30 [A/T] Introduction To Email Security And Filtering

Lecture 31 [A/T] What Are Spam Filters And How Do They Work ?

Lecture 32 [A/P] Introduction to the Email Spam detection AI system

Lecture 33 [A/P] How to load data and work with different data source files?

Lecture 34 [A/P] Analyzing email spam dataset

Lecture 35 [A/P] How to analyze and work with text data?

Lecture 36 [A/P] How to clean and prepare text data for AI/ML?

Lecture 37 [A/P] How to transform email data from text to numbers - Vectorization

Lecture 38 [A/P] Intuition lecture K Nearest Neighbors (KNN) algorithm

Lecture 39 [A/P] Training KNN algorithm to detect spam emails

Lecture 40 [A/P] Creating Spam Detection system using OpenAI API and GPT-4

Section 6: Building A Phishing Detection System With AI

Lecture 41 What, Why, How Of This Section

Lecture 42 [A/T] What is Phishing in the cyber-world?

Lecture 43 [A/T] How To Recognize And Prevent Phishing Attacks

Lecture 44 [A/P] Loading and understanding Phishing dataset

Lecture 45 [A/P] Analyzing Phishing data

Lecture 46 [A/P] Preparing dataset for machine learning/AI

Lecture 47 [A/P] Intuition lecture Decision Trees algorithm

Lecture 48 [A/P] Training Random Forest Algorithm to recognize Phishing websites

Lecture 49 [A/P] How to check the AI system performance - Precision and Recall

Section 7: AI In Network Security

Lecture 50 What, Why, How Of This Section

Lecture 51 [A/T] Introduction To Network Security

Lecture 52 [A/P] Understanding Network Anomaly dataset

Lecture 53 [A/P] Preparing network anomaly dataset - part 1

Lecture 54 [A/P] Preparing network anomaly dataset - part 2

Lecture 55 [A/P] Intuition lecture Logistic Regression algorithm

Lecture 56 [A/P] Training Logistic Regression For Network Monitoring

Lecture 57 [A/P] How to improve an ML/AI algorithm? - Hyperparameter Optimization

Section 8: AI For Malware Detection

Lecture 58 What, Why, How Of This Section

Lecture 59 [A/T] What Is Malware & Different Types Of Malware

Lecture 60 [A/T] How Traditional Systems For Malware Detection work?

Lecture 61 [A/P] Loading and analyzing Malware Dataset

Lecture 62 [A/P] Preparing Malware Dataset for ML/AI

Lecture 63 [A/P] Training Machine Learning based Malware detection system

Lecture 64 [A/P] How to save the best performing Malware Detection Model for later reuse?

Section 9: AI Security Risks

Lecture 65 What, Why, How Of This Section

Lecture 66 [A/T] What is Data Poisoning?

Lecture 67 [A/T] What is Data Bias?

Lecture 68 [A/T] What are general AI Model Vulnerabilities?

Lecture 69 [A/T] What are Ethical Concerns that all of us have?

Section 10: Conclusion and Next Steps

Lecture 70 Thanks For Watching The Course!

Section 11: Appendix A: Introduction To Cyber Security

Lecture 71 Evolution Of Cyber Security

Lecture 72 Categories Of Cyber Attacks

Lecture 73 Security Policies and Procedures

Lecture 74 Cyber Security Tools and Technologies

Lecture 75 Understanding Cyber Security Certifications

Lecture 76 Cyber Security Best Practices

Anyone Interested In Cyber Security,Anyone Interested In Artificial Intelligence,Anyone Interested In Applying AI In Cyber Security,Anyone Who Wants To Learn About Threats and Vulnerabilities In Artificial Intelligence,Anyone Who Wants To Learn How To Combine Python With AI To Develop Cyber Security Tools Like: Network Monitoring System, Phishing Detection System, Malware Detection System, Email Filtering System