A Comparative Study of Traffic Classification Techniques for Smart City Networks [PDF]
Sensors, 2021 Smart city networks involve many applications that impose specific Quality of Service (QoS) requirements, thus representing a challenging scenario for network management.
Razan M. AlZoman, Mohammed J. F. Alenazi
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Explainable Internet Traffic Classification [PDF]
Applied Sciences, 2021 The problem analyzed in this paper deals with the classification of Internet traffic. During the last years, this problem has experienced a new hype, as classification of Internet traffic has become essential to perform advanced network management.
Christian Callegari +3 more
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Software defined networking based network traffic classification using machine learning techniques. [PDF]
Sci RepThe classification of network traffic has become increasingly crucial due to the rapid growth in the number of internet users. Conventional approaches, such as identifying traffic based on port numbers and payload inspection are becoming ineffective due ...
Salau AO, Beyene MM.
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Procedures, Criteria, and Machine Learning Techniques for Network Traffic Classification: A Survey
IEEE Access, 2022 Traffic classification is considered an important research area due to the increasing demand in network users. It not only effectively improve the network service identifications and security issues of the traffic network, but also provide robust ...
Muhammad Sameer Sheikh, Yinqiao Peng
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Robot Communication: Network Traffic Classification Based on Deep Neural Network [PDF]
Frontiers in Neurorobotics, 2021 With the rapid popularization of robots, the risks brought by robot communication have also attracted the attention of researchers. Because current traffic classification methods based on plaintext cannot classify encrypted traffic, other methods based ...
Mengmeng Ge, Xiangzhan Yu, Likun Liu
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Multi-Task Scenario Encrypted Traffic Classification and Parameter Analysis [PDF]
SensorsThe widespread use of encrypted traffic poses challenges to network management and network security. Traditional machine learning-based methods for encrypted traffic classification no longer meet the demands of management and security. The application of
Guanyu Wang, Yijun Gu
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Few-shot traffic classification based on autoencoder and deep graph convolutional networks [PDF]
Scientific ReportsTraffic classification is a crucial technique in network management that aims to identify and manage data packets to optimize network efficiency, ensure quality of service, enhance network security, and implement policy management. As graph convolutional
Shengwei Xu +4 more
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ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification [PDF]
The Web Conference, 2022 Encrypted traffic classification requires discriminative and robust traffic representation captured from content-invisible and imbalanced traffic data for accurate classification, which is challenging but indispensable to achieve network security and ...
Xinjie Lin +5 more
semanticscholar +1 more source
TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification [PDF]
The Web Conference, 2023 Encrypted traffic classification is receiving widespread attention from researchers and industrial companies. However, the existing methods only extract flow-level features, failing to handle short flows because of unreliable statistical properties, or ...
Haozhen Zhang +6 more
semanticscholar +1 more source
Anonymous traffic classification based on three-dimensional Markov image and deep learning [PDF]
Bulletin of the Polish Academy of Sciences: Technical Sciences, 2023 Illegal elements use the characteristics of an anonymous network hidden service mechanism to build a dark network and conduct various illegal activities, which brings a serious challenge to network security.
Xin Tang +5 more
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