Enhancing Phishing Email Detection with Context-Augmented Open Large Language Models
Year: 2024
Type: article
Abstract: Large Language Models offer a promising approach for improving phishing detection through advanced natural language processing. This paper evaluates the effectiveness of context-augmented open LLMs in identifying phishing emails. An approach was developed that combines the methods of Few-Shot Learning and Retrieval-Augmented Generation (RAG) to remarkably improve the performance of LLMs in this area. On this basis, it has been shown that the presented approach can significantly improve the recognition rate even for smaller models.
Source: OJS
Institution: University of Applied Sciences Kaiserslautern
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6958024911