Smart routing based on network traffic classification techniques and considerations

There are several interconnected entities present within the networked data for which the generation of inferences is important. For instance, hyperlinks are used to interconnect the web pages, calls are used to link the phone accounts, and references are used to connect the research papers and so on. Almost every existing application includes networks within it. The daily lives of individuals include social networking, making financial transactions, generating networks that show physical systems and so on. The manner in which the nodes present within the system influence each other can be known through this research. On the basis of observed attributed of an object within the system, another attributed is predicted using new model. The various network traffic classification techniques are reviewed in terms of certain parameters.

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Adversarial Network Traffic: Towards Evaluating the Robustness of Deep-Learning-Based Network Traffic Classification

IEEE Transactions on Network and Service Management ◽

10.1109/tnsm.2021.3052888 ◽

2021 ◽

Vol 18 (2) ◽

pp. 1962-1976

Author(s):

Amir Mahdi Sadeghzadeh ◽

Saeed Shiravi ◽

Rasool Jalili

Keyword(s):

Deep Learning ◽

Network Traffic ◽

Traffic Classification ◽

Adversarial Network ◽

Network Traffic Classification

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Packet Vision: a convolutional neural network approach for network traffic classification

2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) ◽

10.1109/sibgrapi51738.2020.00042 ◽

2020 ◽

Author(s):

Rodrigo Moreira ◽

Larissa Ferreira Rodrigues ◽

Pedro Frosi Rosa ◽

Rui L. Aguiar ◽

Flavio de Oliveira Silva

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Network Traffic ◽

Traffic Classification ◽

Network Approach ◽

Neural Network Approach ◽

Network Traffic Classification

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Multi Class SVM Algorithm with Active Learning for Network Traffic Classification

Expert Systems with Applications ◽

10.1016/j.eswa.2021.114885 ◽

2021 ◽

pp. 114885

Author(s):

Shi Dong

Keyword(s):

Active Learning ◽

Network Traffic ◽

Traffic Classification ◽

Svm Algorithm ◽

Network Traffic Classification

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Network traffic classification via HMM under the guidance of syntactic structure

Computer Networks ◽

10.1016/j.comnet.2012.01.021 ◽

2012 ◽

Vol 56 (6) ◽

pp. 1814-1825 ◽

Cited By ~ 6

Author(s):

ChengGuo Yin ◽

ShuangQing Li ◽

Qi Li

Keyword(s):

Network Traffic ◽

Syntactic Structure ◽

Traffic Classification ◽

Network Traffic Classification

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A novel network traffic classification approach via discriminative feature learning

Proceedings of the 35th Annual ACM Symposium on Applied Computing ◽

10.1145/3341105.3373844 ◽

2020 ◽

Author(s):

Lixin Zhao ◽

Lijun Cai ◽

Aimin Yu ◽

Zhen Xu ◽

Dan Meng

Keyword(s):

Network Traffic ◽

Feature Learning ◽

Traffic Classification ◽

Classification Approach ◽

Discriminative Feature ◽

Network Traffic Classification

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