MSc by Research Studentship: Detection and Analysis of Advanced Phishing Attacks (DAAPA)
Core
Develop a novel, context-aware, domain-specific NLP framework to protect systems against real-world Business Email Compromise and spear-phishing attacks.
Role type
Research MSc student (NLP/ML)
Builds
A Domain-Adapted Transformer Model with Hybrid Linguistic-Contextual and Anomaly-based features
Domain
Cybersecurity, Natural Language Processing, AI-generated content analysis
Deliverable
production ML models
Required skills
NLP, Transformer models, dataset curation, anomaly detection, model interpretability, deep learning evaluation
Preferred skills
Linguistic feature analysis, pragmatic analysis, AI-generated text detection
Technologies
Transformers, deep learning frameworks
Responsibilities
Identify and characterize linguistic and stylistic features in phishing attacks; develop and curate a large-scale dataset of malicious and benign communications; design and implement the detection model; evaluate the model against traditional deep learning approaches; develop an interpretability mechanism for classification decisions.
