… networking apply deep learning models for Network Traffic Monitoring and Analysis (NTMA)
applications, eg, traffic … comprehensive review on applications of deep learning in NTMA. We …

… -art deep learning techniques. Second, we identify the various network traffic control themes
where deep learning … In our survey, for each of these networking themes, we provide a brief …

… Therefore, network traffic analysis is considered vital for improving networks operation and
… different machine learning approaches for traffic analysis. Increased network traffic and the …

… networking field is still new to deep learning and needs more research. If we can design
appropriate deep learning structures to selflearn network traffic control, … utilize the deep learning …

… We find their work helpful in its analysis of deep learning architectures for network traffic,
as many of their conclusions can also be applied to the SNI classification problem. …

… deep learning approach for auto-learning the traffic features and profiling traffic directly from
the raw traffic … 1D-CNN is also widely used for network traffic analysis, eg, [19], including this …

… The main contribution of this article is (i) proposed a deep learning neural network approach
for DS2OS traffic traces data set; (ii) the proposed model has an undeviating effect on the …

… After we parse the input network log instances, we perform the subsequent analysis steps,
including the design and evaluation of semi-supervised Deep Learning (DL) anomaly …

… Demand for enabling accurate mobile app identification is coming as it is an essential step
to improve a multitude of network services: accounting, security monitoring, traffic forecasting, …

… deep learning based traffic classification and prediction in SDN is explained in [21]. Traffic
analysis and routing optimization with deep learning … from rule-based network traffic control to …