most citedSAFE: Self-Supervised Anomaly Detection Framework for Intrusion Detection

2 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2025

TS-OOD: Evaluating Time-Series Out-of-Distribution Detection and Prospective Directions for Progress

Onat Gungor, Amanda Sofie Rios, Nilesh Ahuja +1

Detecting out-of-distribution (OOD) data is a fundamental challenge in the deployment of machine learning models. From a security standpoint, this is particularly important because…

cs.CR2025

CND-IDS: Continual Novelty Detection for Intrusion Detection Systems

Sean Fuhrman, Onat Gungor, Tajana Rosing

Intrusion detection systems (IDS) play a crucial role in IoT and network security by monitoring system data and alerting to suspicious activities. Machine learning (ML) has emerged…

cs.CR2025★ 2 cited

SAFE: Self-Supervised Anomaly Detection Framework for Intrusion Detection

Elvin Li, Zhengli Shang, Onat Gungor +1

The proliferation of IoT devices has significantly increased network vulnerabilities, creating an urgent need for effective Intrusion Detection Systems (IDS). Machine Learning-base…