4 papers
Attribution-Driven Explainable Intrusion Detection with Encoder-Based Large Language Models
Umesh Biswas, Shafqat Hasan, Syed Mohammed Farhan +2
Software-Defined Networking (SDN) improves network flexibility but also increases the need for reliable and interpretable intrusion detection. Large Language Models (LLMs) have rec…
Learning Robust Representations for Malicious Content Detection via Contrastive Sampling and Uncertainty Estimation
Elias Hossain, Umesh Biswas, Charan Gudla +1
We propose the Uncertainty Contrastive Framework (UCF), a Positive-Unlabeled (PU) representation learning framework that integrates uncertainty-aware contrastive loss, adaptive tem…
Applications of Positive Unlabeled (PU) and Negative Unlabeled (NU) Learning in Cybersecurity
Robert Dilworth, Charan Gudla
This paper explores the relatively underexplored application of Positive Unlabeled (PU) Learning and Negative Unlabeled (NU) Learning in the cybersecurity domain. While these semi-…
Harnessing PU Learning for Enhanced Cloud-based DDoS Detection: A Comparative Analysis
Robert Dilworth, Charan Gudla
This paper explores the application of Positive-Unlabeled (PU) learning for enhanced Distributed Denial-of-Service (DDoS) detection in cloud environments. Utilizing the $\texttt{BC…