Hands-on Lab

Introduction

This lab demonstrates how a GAN can generate deepfake phishing emails, helping students understand the potential risks of generative AI in phishing attacks.

Objectives

- Understand GAN architecture and its components.

- Train a GAN to generate phishing emails.

- Compare generated emails to real phishing emails.

Lab Steps

1. Dataset Preparation:

   - Load the phishing email dataset.

   - Extract and vectorize email text features.

2. Train the GAN:

   - Train the GAN’s generator and discriminator.

   - Monitor the generator's ability to create realistic phishing emails.

3. Evaluate Generated Emails:

   - Compare real and generated emails’ distributions.

   - Measure the quality of generated emails.

4. Discussion:

   - Discuss the implications of deepfake phishing emails in cybersecurity.