Paper Info
Title
Quality Estimation Framework for Encrypted Traffic (Q2ET)
Abstract
In the coming years, the development of the Internet of Things (IoT) will have relevance for transport, environment, health care, smart cities and also multimedia services (Multimedia Internet of Things (MIoT)). Nowadays, many ISP (Internet Service Provider) encrypt the data to make it secure during the transmission. However, it imposes some obstacles for the NSP (Network Service Provider) because of the lack of visibility for operators into network traffic. To resolve these issues, we proposed the Quality Estimation Framework for Encrypted Traffic (Q2ET) containing a classification module and a QoE assessment module. The first module inherited from our previous research works to classify the encrypted network traffic using CNN (Convolutional Neural Network). The second one applies the objective and subjective methods based on the statistical analysis and machine learning methods that combine application and network parameters to calculate user's QoE (Quality of Experience) in terms of MOS (Mean Opinion Score). The Q2ET allows the NSP to monitor the user's QoE to take the appropriate decisions when the QoE degradation happens in the network systems.
Year
DOI
Venue
2019
10.1109/GLOBECOM38437.2019.9014234
2019 IEEE Global Communications Conference (GLOBECOM)
Keywords
DocType
ISSN
MOS,mean opinion score,CNN,ISP,MIoT,multimedia services,quality estimation framework,internet service provider,network systems,quality of experience,network parameters,machine learning methods,statistical analysis,convolutional neural network,encrypted network traffic,QoE assessment module,classification module,network service provider,NSP,multimedia Internet of Things,smart cities,health care,Q2ET
Conference
1930-529X
ISBN
Citations 
PageRank 
978-1-7281-0963-3
0
0.34
References 
Authors
11
5
Name
Order
Citations
PageRank
Lamine Amour172.34
Van Tong212.04
Sami Souihi3529.99
Hai Anh Tran4548.92
Abdelhamid Mellouk567975.86