KGV: Integrating Large Language Models with Knowledge Graphs for Cyber Threat Intelligence Credibility Assessment
Authors: Zongzong Wu, Fengxiao Tang, Ming Zhao, Yufeng Li | Published: 2024-08-15
Dataset Generation
SAGE-RT: Synthetic Alignment data Generation for Safety Evaluation and Red Teaming
Authors: Anurakt Kumar, Divyanshu Kumar, Jatan Loya, Nitin Aravind Birur, Tanay Baswa, Sahil Agarwal, Prashanth Harshangi | Published: 2024-08-14
From ML to LLM: Evaluating the Robustness of Phishing Webpage Detection Models against Adversarial Attacks
Authors: Aditya Kulkarni, Vivek Balachandran, Dinil Mon Divakaran, Tamal Das | Published: 2024-07-29 | Updated: 2025-03-15
MLLMGuard: A Multi-dimensional Safety Evaluation Suite for Multimodal Large Language Models
Authors: Tianle Gu, Zeyang Zhou, Kexin Huang, Dandan Liang, Yixu Wang, Haiquan Zhao, Yuanqi Yao, Xingge Qiao, Keqing Wang, Yujiu Yang, Yan Teng, Yu Qiao, Yingchun Wang | Published: 2024-06-11 | Updated: 2024-06-13
Differentially Private Tabular Data Synthesis using Large Language Models
Authors: Toan V. Tran, Li Xiong | Published: 2024-06-03
Federated Domain-Specific Knowledge Transfer on Large Language Models Using Synthetic Data
Authors: Haoran Li, Xinyuan Zhao, Dadi Guo, Hanlin Gu, Ziqian Zeng, Yuxing Han, Yangqiu Song, Lixin Fan, Qiang Yang | Published: 2024-05-23
LLMPot: Dynamically Configured LLM-based Honeypot for Industrial Protocol and Physical Process Emulation
Authors: Christoforos Vasilatos, Dunia J. Mahboobeh, Hithem Lamri, Manaar Alam, Michail Maniatakos | Published: 2024-05-09 | Updated: 2025-05-19
Analysis and prevention of AI-based phishing email attacks
Authors: Chibuike Samuel Eze, Lior Shamir | Published: 2024-05-08
SEvenLLM: Benchmarking, Eliciting, and Enhancing Abilities of Large Language Models in Cyber Threat Intelligence
Authors: Hangyuan Ji, Jian Yang, Linzheng Chai, Chaoren Wei, Liqun Yang, Yunlong Duan, Yunli Wang, Tianzhen Sun, Hongcheng Guo, Tongliang Li, Changyu Ren, Zhoujun Li | Published: 2024-05-06 | Updated: 2024-06-03
Ransomware Detection and Classification Using Random Forest: A Case Study with the UGRansome2024 Dataset
Authors: Peace Azugo, Hein Venter, Mike Wa Nkongolo | Published: 2024-04-19