4 citations · 6 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
E-QUARTIC: Energy Efficient Edge Ensemble of Convolutional Neural Networks for Resource-Optimized Learning
Le Zhang, Onat Gungor, Flavio Ponzina +1
Ensemble learning is a meta-learning approach that combines the predictions of multiple learners, demonstrating improved accuracy and robustness. Nevertheless, ensembling models li…
RES-HD: Resilient Intelligent Fault Diagnosis Against Adversarial Attacks Using Hyper-Dimensional Computing
Onat Gungor, Tajana Rosing, Baris Aksanli
Industrial Internet of Things (I-IoT) enables fully automated production systems by continuously monitoring devices and analyzing collected data. Machine learning methods are commo…