16 citations · 18 across the 10 of their papers we have counts for
4 papers · 1 filter
AutoFlow: An Autoencoder-based Approach for IP Flow Record Compression with Minimal Impact on Traffic Classification
Adrian Pekar
Network monitoring generates massive volumes of IP flow records, posing significant challenges for storage and analysis. This paper presents a novel deep learning-based approach to…
Early Detection of Network Service Degradation: An Intra-Flow Approach
Balint Bicski, Adrian Pekar
This research presents a novel method for predicting service degradation (SD) in computer networks by leveraging early flow features. Our approach focuses on the observable (O) seg…
Early-Stage Anomaly Detection: A Study of Model Performance on Complete vs. Partial Flows
Adrian Pekar, Richard Jozsa
This study investigates the efficacy of machine learning models in network security threat detection through the critical lens of partial versus complete flow information, addressi…
Evaluating ML-Based Anomaly Detection Across Datasets of Varied Integrity: A Case Study
Adrian Pekar, Richard Jozsa
Cybersecurity remains a critical challenge in the digital age, with network traffic flow anomaly detection being a key pivotal instrument in the fight against cyber threats. In thi…