3 papers
cs.CR2025
How Can We Effectively Use LLMs for Phishing Detection?: Evaluating the Effectiveness of Large Language Model-based Phishing Detection Models
Fujiao Ji, Doowon Kim
Large language models (LLMs) have emerged as a promising phishing detection mechanism, addressing the limitations of traditional deep learning-based detectors, including poor gener…
cs.CR2025
A Systematic Evaluation of Parameter-Efficient Fine-Tuning Methods for the Security of Code LLMs
Kiho Lee, Jungkon Kim, Doowon Kim +1
Code-generating Large Language Models (LLMs) significantly accelerate software development. However, their frequent generation of insecure code presents serious risks. We present a…
cs.CR2025
Registration, Detection, and Deregistration: Analyzing DNS Abuse for Phishing Attacks
Kyungchan Lim, Raffaele Sommese, Mattis Jonker +3
Phishing continues to pose a significant cybersecurity threat. While blocklists currently serve as a primary defense, due to their reactive, passive nature, these delayed responses…