Cover Image

Evaluating ML-Based Anomaly Detection Across Datasets of Varied Integrity: A Case Study

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pekar, Adrian, Jozsa, Richard
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Networking and Internet Architecture
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Taming Volatility: Stable and Private QUIC Classification with Federated Learning
by: Jozsa, Richard, et al.
Published: (2025)

Early Detection of Network Service Degradation: An Intra-Flow Approach
by: Bicski, Balint, et al.
Published: (2024)

AutoFlow: An Autoencoder-based Approach for IP Flow Record Compression with Minimal Impact on Traffic Classification
by: Pekar, Adrian
Published: (2024)

Benchmarking Anomaly Detection Across Heterogeneous Cloud Telemetry Datasets
by: Islam, Mohammad Saiful, et al.
Published: (2026)

On the Feasibility of Inter-Flow Service Degradation Detection
by: Bicski, Balint, et al.
Published: (2025)

Tutorial on Flow-Based Network Traffic Classification Using Machine Learning
by: Pekar, Adrian, et al.
Published: (2026)

CNN+Transformer Based Anomaly Traffic Detection in UAV Networks for Emergency Rescue
by: Han, Yulu, et al.
Published: (2025)

Develop End-to-End Anomaly Detection System
by: Mengoli, Emanuele, et al.
Published: (2024)

Binary VPN Traffic Detection Using Wavelet Features and Machine Learning
by: Razooqi, Yasameen Sajid, et al.
Published: (2025)

ML-Enabled Eavesdropper Detection in Beyond 5G IIoT Networks
by: Bartsioka, Maria-Lamprini A., et al.
Published: (2025)

Proof of AutoML: SDN based Secure Energy Trading with Blockchain in Disaster Case
by: Toprak, Salih, et al.
Published: (2025)

Intrusion Detection on Resource-Constrained IoT Devices with Hardware-Aware ML and DL
by: Diab, Ali, et al.
Published: (2025)

Quantum Gated Recurrent GAN with Gaussian Uncertainty for Network Anomaly Detection
by: Hammami, Wajdi, et al.
Published: (2025)

Routing for Large ML Models
by: Cohen, Ofir, et al.
Published: (2025)

Multi-Scale Convolutional LSTM with Transfer Learning for Anomaly Detection in Cellular Networks
by: Noonari, Nooruddin, et al.
Published: (2024)

ALPHA: LLM-Enabled Active Learning for Human-Free Network Anomaly Detection
by: Luo, Xuanhao, et al.
Published: (2025)

Morphlux: Transforming Torus Fabrics for Efficient Multi-tenant ML
by: Kumar, Abhishek Vijaya, et al.
Published: (2025)

Enhancing Anomaly-Based Intrusion Detection Systems with Process Mining
by: Vitale, Francesco, et al.
Published: (2026)

Network Calculus with Flow Prolongation -- A Feedforward FIFO Analysis enabled by ML
by: Geyer, Fabien, et al.
Published: (2022)

Credence: Augmenting Datacenter Switch Buffer Sharing with ML Predictions
by: Addanki, Vamsi, et al.
Published: (2024)

Drift-Based Dataset Stability Benchmark
by: Soukup, Dominik, et al.
Published: (2025)

LUMION: Fast Fault Recovery for ML Jobs Using Programmable Optical Fabrics
by: Kumar, Abhishek Vijaya, et al.
Published: (2025)

Optimal Resource Allocation for ML Model Training and Deployment under Concept Drift
by: Beytur, Hasan Burhan, et al.
Published: (2025)

Optimizing Storage Overhead of User Behavior Log for ML-embedded Mobile Apps
by: Gong, Chen, et al.
Published: (2025)

DBLP: Phase-Aware Bounded-Loss Transport for Burst-Resilient Distributed ML Training
by: Ma, Zechen, et al.
Published: (2026)

Network Traffic Analysis with Process Mining: The UPSIDE Case Study
by: Vitale, Francesco, et al.
Published: (2025)

Anomaly Detection for IoT Global Connectivity
by: Iglesias, Jesus Omaña, et al.
Published: (2025)

Ordered Topological Deep Learning: a Network Modeling Case Study
by: Bernárdez, Guillermo, et al.
Published: (2025)

Deep Learning for Network Anomaly Detection under Data Contamination: Evaluating Robustness and Mitigating Performance Degradation
by: Nkashama, D'Jeff K., et al.
Published: (2024)

NeuralEmu: in situ Measurement-Driven, ML-based, High-Fidelity 5G Network Emulation
by: Wan, Haoran, et al.
Published: (2026)

ML-based handover prediction over a real O-RAN deployment using RAN Intelligent controller
by: Dzaferagic, Merim, et al.
Published: (2024)

Multi-Span Optical Power Spectrum Evolution Modeling using ML-based Multi-Decoder Attention Framework
by: Raj, Agastya, et al.
Published: (2025)

Root Cause Analysis of Anomalies in 5G RAN Using Graph Neural Network and Transformer
by: Hasan, Antor, et al.
Published: (2024)

A Transfer Learning Framework for Anomaly Detection in Multivariate IoT Traffic Data
by: Rezakhani, Mahshid, et al.
Published: (2025)

AdapShare: An RL-Based Dynamic Spectrum Sharing Solution for O-RAN
by: Gopal, Sneihil, et al.
Published: (2024)

Synthesizing Diverse Network Flow Datasets with Scalable Dynamic Multigraph Generation
by: Grayeli, Arya, et al.
Published: (2025)

Machine Learning-Driven Anomaly Detection for 5G O-RAN Performance Metrics
by: Azkaei, Babak, et al.
Published: (2025)

AI/ML Based Detection and Categorization of Covert Communication in IPv6 Network
by: Rahman, Mohammad Wali Ur, et al.
Published: (2025)

Data Matters: The Case of Predicting Mobile Cellular Traffic
by: Vesselinova, Natalia, et al.
Published: (2024)

Evasion Adversarial Attacks Remain Impractical Against ML-based Network Intrusion Detection Systems, Especially Dynamic Ones
by: elShehaby, Mohamed, et al.
Published: (2023)