Binary VPN Traffic Detection Using Wavelet Features and Machine Learning.

Incremental federated learning for traffic flow classification in heterogeneous data scenarios.

Integrating the Skies for 6G: Techno-Economic Considerations of LEO, HAPS, and UAV Technologies.

P4toNFV: Offloading from P4 switches to NFV in programmable data planes.

AutoFlow: An Autoencoder-based Approach for IP Flow Record Compression with Minimal Impact on Traffic Classification.

Early-Stage Anomaly Detection: A Study of Model Performance on Complete vs. Partial Flows.

Evaluating ML-based anomaly detection across datasets of varied integrity: A case study.

Unveiling Latency-Induced Service Degradation: A Methodological Approach With Dataset.

Simple Heuristics as a Viable Alternative to Machine Learning-Based Anomaly Detection in Industrial IoT.

Public transport congestion detection using incremental learning.

Towards threshold-agnostic heavy-hitter classification.

NFStream: A flexible network data analysis framework.

Quality-enabled decentralized IoT architecture with efficient resources utilization.

Knowledge Discovery: Can It Shed New Light on Threshold Definition for Heavy-Hitter Detection?

Application Domain-Based Overview of IoT Network Traffic Characteristics.

A non-intrusive Smart metering system: Analytics and simulation of power consumption.

Smart User Consumption Profiling: Incremental Learning-Based OTT Service Degradation.

Scalable Architecture for SDN Traffic Classification.

Adaptive Aggregation of Flow Records.

Optimalizácia monitorovania sieťovej prevádzky.

Overview and insight into the MONICA research group.