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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CBD: A Deep-Learning-Based Scheme for Encrypted Traffic Classification with a General Pre-Training Method [PDF]
Sensors, 2021 With the rapid increase in encrypted traffic in the network environment and the increasing proportion of encrypted traffic, the study of encrypted traffic classification has become increasingly important as a part of traffic analysis.
Xinyi Hu +3 more
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FedETC: Encrypted traffic classification based on federated learning. [PDF]
HeliyonThe current popular traffic classification methods based on feature engineering and machine learning are difficult to obtain suitable traffic feature sets for multiple traffic classification tasks. Besides, data privacy policies prohibit network operators from collecting and sharing traffic data that might compromise user privacy.
Jin Z +5 more
europepmc +4 more sources
Encrypted traffic classification encoder based on lightweight graph representation [PDF]
Scientific ReportsIn recent years, traffic encryption technology has been widely adopted for user information protection, leading to a substantial increase in encrypted traffic in communication networks.
ZhenWei Chen, XiaoXu Wei, YongSheng Wang
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PACKETCLIP: multi-modal embedding of network traffic and language for cybersecurity reasoning [PDF]
Frontiers in Artificial IntelligenceTraffic classification is vital for cybersecurity, yet encrypted traffic poses significant challenges. We introduce PACKETCLIP which is a multi-modal framework combining packet data with natural language semantics through contrastive pre-training and ...
Ryozo Masukawa +7 more
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An encrypted traffic classification method based on autoencoders and convolutional neural networks. [PDF]
PLoS ONETo solve the problems of existing encrypted traffic classification methods, such as the need for large-scale training data, high computational costs, and poor generalization ability, an encrypted traffic classification method based on autoencoders and ...
Shengwei Xu +3 more
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Encrypted Network Traffic Analysis and Classification Utilizing Machine Learning
SensorsEncryption is a fundamental security measure to safeguard data during transmission to ensure confidentiality while at the same time posing a great challenge for traditional packet and traffic inspection.
Ibrahim A. Alwhbi +2 more
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Encrypted Traffic Classification Method Based on Multi-Layer Bidirectional SRU and Attention Model [PDF]
Jisuanji gongcheng, 2022 The encrypted traffic classification method based on traditional Recurrent Neural Network(RNN) typically have poor parallelism and low efficiency.To quickly and accurately classify encrypted traffic, a classification method for encrypted traffic based on
ZHANG Surong, BU Youjun, CHEN Bo, SUN Chongxin, WANG Han, HU Xianjun
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Semi-2DCAE: a semi-supervision 2D-CNN AutoEncoder model for feature representation and classification of encrypted traffic [PDF]
PeerJ Computer Science, 2023 Traffic classification is essential in network-related areas such as network management, monitoring, and security. As the proportion of encrypted internet traffic rises, the accuracy of port-based and DPI-based traffic classification methods has declined.
Jun Cui +4 more
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Edge Intelligence Based Identification and Classification of Encrypted Traffic of Internet of Things
IEEE Access, 2021 A detection model of Internet of Things encrypted traffic based on edge intelligence is proposed in the paper, which can reduce the communication times of distributed Internet of Things gateways in the process of edge intelligence as well as the ...
Yue Zhao +5 more
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