A review of generative models in generating synthetic attack data for cybersecurity

G Agrawal, A Kaur, S Myneni - Electronics, 2024 - mdpi.com
The ability of deep learning to process vast data and uncover concealed malicious patterns
has spurred the adoption of deep learning methods within the cybersecurity domain …

A comprehensive overview of large language models (llms) for cyber defences: Opportunities and directions

M Hassanin, N Moustafa - ar** large language models for attacks against black-box neural ranking models
YA Liu, R Zhang, J Guo, M de Rijke, Y Fan… - arxiv preprint arxiv …, 2024 - arxiv.org
Neural ranking models (NRMs) have been shown to be highly effective in terms of retrieval
performance. Unfortunately, they have also displayed a higher degree of sensitivity to …

Enhancing DevSecOps practice with Large Language Models and Security Chaos Engineering

M Bedoya, S Palacios, D Díaz-López… - International Journal of …, 2024 - Springer
Recently, the DevSecOps practice has improved companies' agile production of secure
software, reducing problems and improving return on investment. However, overreliance on …

Semantic analysis of phishing emails leading to ransomware with chatgpt

H Fujima, K Takeuchi, T Kumamoto - 2023 - researchsquare.com
Ransomware attacks have rapidly emerged as crippling threats to organizational stability
and business continuity. This study conducts an in-depth analysis of real-world phishing …

ChatPhishDetector: Detecting Phishing Sites Using Large Language Models

T Koide, H Nakano, D Chiba - IEEE Access, 2024 - ieeexplore.ieee.org
Large Language Models (LLMs), such as ChatGPT, are significantly impacting various
fields. While LLMs have been extensively studied for code generation and text synthesis …