A survey of techniques for mobile service encrypted traffic classification using deep learning

P Wang, X Chen, F Ye, Z Sun - Ieee Access, 2019 - ieeexplore.ieee.org
The rapid adoption of mobile devices has dramatically changed the access to various
networking services and led to the explosion of mobile service traffic. Mobile service traffic …

Imbalanced data preprocessing techniques for machine learning: a systematic mapping study

V Werner de Vargas, JA Schneider Aranda… - … and Information Systems, 2023 - Springer
Abstract Machine Learning (ML) algorithms have been increasingly replacing people in
several application domains—in which the majority suffer from data imbalance. In order to …

PacketCGAN: Exploratory study of class imbalance for encrypted traffic classification using CGAN

P Wang, S Li, F Ye, Z Wang… - ICC 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
With the popularity of Deep Learning (DL), researchers have begun to apply DL to tackle
with encrypted traffic classification problems. Although these methods can automatically …

CETAnalytics: Comprehensive effective traffic information analytics for encrypted traffic classification

C Dong, C Zhang, Z Lu, B Liu, B Jiang - Computer Networks, 2020 - Elsevier
Encrypted traffic classification is of great significance for advanced network services. Though
encryption methods seem unbroken in protecting users' privacy, existing studies have …

[HTML][HTML] Multiclass imbalanced and concept drift network traffic classification framework based on online active learning

W Liu, C Zhu, Z Ding, H Zhang, Q Liu - Engineering Applications of Artificial …, 2023 - Elsevier
The complex problems of multiclass imbalance, virtual or real concept drift, concept
evolution, high-speed traffic streams and limited label cost budgets pose severe challenges …

Combating imbalance in network traffic classification using GAN based oversampling

Y Guo, G Xiong, Z Li, J Shi, M Cui… - 2021 IFIP Networking …, 2021 - ieeexplore.ieee.org
With the proliferation of encrypted traffic, machine learning (ML) based network traffic
classification (NTC) has become the mainstream method. However, most studies ignored …

FLOWGAN: Unbalanced network encrypted traffic identification method based on GAN

ZX Wang, P Wang, X Zhou, SH Li… - 2019 IEEE Intl Conf on …, 2019 - ieeexplore.ieee.org
It is crucial to accurately identify the type of traffic and application so that it can enable
various policy-driven network management and security monitoring. However, with the …

Machine learning algorithm in network traffic classification

SM Rachmawati, DS Kim, JM Lee - … Conference on Information …, 2021 - ieeexplore.ieee.org
Network traffic classification plays an important role in various network functions such as
network security issues and network management. In addition to port-based and payload …

Traffic identification model based on generative adversarial deep convolutional network

S Dong, Y Xia, T Peng - Annals of Telecommunications, 2022 - Springer
With the rapid development of network technology, the Internet has accelerated the
generation of network traffic, which has made network security a top priority. In recent years …

CENTIME: a direct comprehensive traffic features extraction for encrypted traffic classification

W Maonan, Z Kangfeng, X Ning… - 2021 IEEE 6th …, 2021 - ieeexplore.ieee.org
With the rapid development of the network, encrypted traffic classification plays a vital role in
guaranteeing the quality of network services and ensuring the security of the network …