About
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.
Benchmarks
Datasets
Greatest papers with code
Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning
Our proposed scheme, called "Deep Packet," can handle both \emph{traffic characterization} in which the network traffic is categorized into major classes (\eg, FTP and P2P) and application identification in which end-user applications (\eg, BitTorrent and Skype) identification is desired.
Multitask Learning for Network Traffic Classification
We show that with a large amount of easily obtainable data samples for bandwidth and duration prediction tasks, and only a few data samples for the traffic classification task, one can achieve high accuracy.
MALWARE DETECTION MULTI-TASK LEARNING TRAFFIC CLASSIFICATION
Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles
• fkthi/OpenTrafficMonitoringPlus
• 
A robust object detection is crucial for reliable results, hence the state-of-the-art deep neural network Mask-RCNN is applied for that purpose.
DRONE-BASED OBJECT TRACKING ROBUST OBJECT DETECTION TRAFFIC CLASSIFICATION