… , we discuss Networktraffic classification techniques and discuss. And then we discuss comparative analysis of four machinelearning classifiers. We first capture networktraffic using …
Z Fan, R Liu - 2017 International Symposium on Wireless …, 2017 - ieeexplore.ieee.org
… costs and identify encrypted traffic easily. This paper investigates traffic classification techniques based on machinelearning. We consider two machinelearning algorithms, SVM and K-…
T Bujlow, T Riaz, JM Pedersen - … on computing, networking and …, 2012 - ieeexplore.ieee.org
… 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 …
… machinelearning algorithms on network traffic data for accurate identification of IoT devices connected to a network. … , we collected and labeled networktraffic data from nine distinct IoT …
… traffic propagating via the premises of Network … networktraffic scanners capable of cleaning traffic from known malicious code. The remaining traffic is monitored and MachineLearning (…
… , is considered a challenge causing different networking inefficiencies. To overcome these … of networks, called NetworkTraffic Monitoring and Analysis (NTMA). NetworkTraffic …
S Patel, A Gupta, S Kumari, M Singh… - … and Networking …, 2018 - ieeexplore.ieee.org
… Networktraffic classification techniques are discussed in this paper to enhance some idea about MachineLearning algorithms for networktraffic … which MachineLearning algorithm is …
… network protocols. We employ three supervised machinelearning (ML) algorithms, Bayesian Networks… types of Internet traffic including peer-to-peer (P2P) and content delivery (Akamai) …
… use of machinelearning techniques to identify networktraffic … on a set of traffic traces from different networks. We investigate … encrypted (or non encrypted) networktraffic. In this research, …