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Traffic Classification

Traffic Classification is a task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Classification can be used for several purposes including policy enforcement and control or QoS management.

Source: Classification of Traffic Using Neural Networks by Rejecting: a Novel Approach in Classifying VPN Traffic

Papers

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Showing 76–100 of 110 papers

TitleStatusHype
Anomaly Detection Framework Using Rule Extraction for Efficient Intrusion Detection—0
Applications of Artificial Intelligence, Machine Learning and related techniques for Computer Networking Systems—0
Augmentation Scheme for Dealing with Imbalanced Network Traffic Classification Using Deep Learning—0
CBR - Boosting Adaptive Classification By Retrieval of Encrypted Network Traffic with Out-of-distribution—0
CGNN: Traffic Classification with Graph Neural Network—0
Mobile Traffic Classification through Physical Channel Fingerprinting: a Deep Learning Approach—0
Classification of Traffic Using Neural Networks by Rejecting: a Novel Approach in Classifying VPN Traffic—0
Darknet Traffic Classification and Adversarial Attacks—0
Data Augmentation for Traffic Classification—0
Deep Learning and Traffic Classification: Lessons learned from a commercial-grade dataset with hundreds of encrypted and zero-day applications—0
Deep Learning Approaches for Network Traffic Classification in the Internet of Things (IoT): A Survey—0
Deep Learning for Encrypted Traffic Classification and Unknown Data Detection—0
The Adversarial Machine Learning Conundrum: Can The Insecurity of ML Become The Achilles' Heel of Cognitive Networks?—0
Time-Distributed Feature Learning in Network Traffic Classification for Internet of Things—0
Toward Generative Data Augmentation for Traffic Classification—0
Towards a graph-based foundation model for network traffic analysis—0
Towards Intelligent Network Management: Leveraging AI for Network Service Detection—0
From Classification to Optimization: Slicing and Resource Management with TRACTOR—0
Traffic Analytics Development Kits (TADK): Enable Real-Time AI Inference in Networking Apps—0
Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges—0
VINEVI: A Virtualized Network Vision Architecture for Smart Monitoring of Heterogeneous Applications and Infrastructures—0
Real-time Traffic Classification for 5G NSA Encrypted Data Flows With Physical Channel Records—0
Real Time Video Quality Representation Classification of Encrypted HTTP Adaptive Video Streaming - the Case of Safari—0
Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification—0
Packet Inspection Transformer: A Self-Supervised Journey to Unseen Malware Detection with Few Samples—0
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