A Data-Centric Approach to Context-Aware Email Scenario Generation via Adversarially Guided Synthetic Data Curation

The thesis investigates how adversarially guided data curation (GAN-like) can be used to control the quality, diversity, and distributional properties of context-aware Large Language Model (LLM) driven Phishing text generation.