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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 51–100 of 110 papers

TitleStatusHype
Malware Traffic Classification: Evaluation of Algorithms and an Automated Ground-truth Generation Pipeline—0
Many or Few Samples? Comparing Transfer, Contrastive and Meta-Learning in Encrypted Traffic Classification—0
MERLOT: A Distilled LLM-based Mixture-of-Experts Framework for Scalable Encrypted Traffic Classification—0
Multi-view Multi-label Anomaly Network Traffic Classification based on MLP-Mixer Neural Network—0
Net2Vec: Deep Learning for the Network—0
NetFlowGen: Leveraging Generative Pre-training for Network Traffic Dynamics—0
Network Traffic Anomaly Detection Method Based on Multi scale Residual Feature—0
Network Traffic Classification Using Machine Learning, Transformer, and Large Language Models—0
Non-uniformity is All You Need: Efficient and Timely Encrypted Traffic Classification With ECHO—0
OMINACS: Online ML-Based IoT Network Attack Detection and Classification System—0
On Designing Machine Learning Models for Malicious Network Traffic Classification—0
To Store or Not? Online Data Selection for Federated Learning with Limited Storage—0
On the Local Cache Update Rules in Streaming Federated Learning—0
Outlier detection on network flow analysis—0
PacketCLIP: Multi-Modal Embedding of Network Traffic and Language for Cybersecurity Reasoning—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
TEST: an End-to-End Network Traffic Examination and Identification Framework Based on Spatio-Temporal Features Extraction—0
Time-Distributed Feature Learning for Internet of Things Network Traffic Classification—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
ITCM: A Real Time Internet Traffic Classifier Monitor—0
Cellular Traffic Prediction and Classification: a comparative evaluation of LSTM and ARIMA—0
A Natural Language-Inspired Multi-label Video Streaming Traffic Classification Method Based on Deep Neural Networks—0
When Simple Model Just Works: Is Network Traffic Classification in Crisis?—0
Energy-Efficient Deep Learning for Traffic Classification on Microcontrollers—0
Active Learning for Network Traffic Classification: A Technical Study—0
Active Learning Framework to Automate NetworkTraffic Classification—0
A First Look at Class Incremental Learning in Deep Learning Mobile Traffic Classification—0
A General Approach for Traffic Classification in Wireless Networks Using Deep Learning—0
Malicious Requests Detection with Improved Bidirectional Long Short-term Memory Neural Networks—0
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
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