… traffic, and more accurate Quality of Service management. ML is fast becoming a key tool to
build traffic classification solutions in real network traffic … work in the traffic classification field. …

… , we discuss Network traffic classification techniques and discuss. And then we discuss
comparative analysis of four machine learning classifiers. We first capture network traffic using …

… costs and identify encrypted traffic easily. This paper investigates traffic classification techniques
based on machine learning. We consider two machine learning algorithms, SVM and K-…

… Networks requires therefore knowledge about types of applications forming current network
traffic. To overcome the drawbacks of existing methods for traffic classification, usage of C5.0 …

… traffic propagating via the premises of Network … network traffic scanners capable of cleaning
traffic from known malicious code. The remaining traffic is monitored and Machine Learning (…

… , is considered a challenge causing different networking inefficiencies. To overcome
these … of networks, called Network Traffic Monitoring and Analysis (NTMA). Network Traffic …

… machine learning algorithms on network traffic data for accurate identification of IoT devices
connected to a network. … , we collected and labeled network traffic data from nine distinct IoT …

… Network traffic classification techniques are discussed in this paper to enhance some idea
about Machine Learning algorithms for network traffic … which Machine Learning algorithm is …

… network protocols. We employ three supervised machine learning (ML) algorithms, Bayesian
Networks… types of Internet traffic including peer-to-peer (P2P) and content delivery (Akamai) …

… use of machine learning techniques to identify network traffic … on a set of traffic traces from
different networks. We investigate … encrypted (or non encrypted) network traffic. In this research, …