Enhancing Phishing Email Identification with Large Language Models
This addresses phishing detection for cybersecurity, but appears incremental as it applies existing LLMs to a known domain.
The paper tackled the problem of detecting phishing emails by evaluating the efficacy of large language models (LLMs), achieving high accuracy and precision while providing interpretable evidence for decisions.
Phishing has long been a common tactic used by cybercriminals and continues to pose a significant threat in today's digital world. When phishing attacks become more advanced and sophisticated, there is an increasing need for effective methods to detect and prevent them. To address the challenging problem of detecting phishing emails, researchers have developed numerous solutions, in particular those based on machine learning (ML) algorithms. In this work, we take steps to study the efficacy of large language models (LLMs) in detecting phishing emails. The experiments show that the LLM achieves a high accuracy rate at high precision; importantly, it also provides interpretable evidence for the decisions.