Towards the deployment of machine learning solutions in network traffic classification: A systematic survey

F Pacheco, E Exposito, M Gineste… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
Traffic analysis is a compound of strategies intended to find relationships, patterns,
anomalies, and misconfigurations, among others things, in Internet traffic. In particular, traffic …

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 …

A survey of methods for encrypted traffic classification and analysis

P Velan, M Čermák, P Čeleda… - International Journal of …, 2015 - Wiley Online Library
With the widespread use of encrypted data transport, network traffic encryption is becoming
a standard nowadays. This presents a challenge for traffic measurement, especially for …

A review on machine learning–based approaches for Internet traffic classification

O Salman, IH Elhajj, A Kayssi, A Chehab - Annals of Telecommunications, 2020 - Springer
Traffic classification acquired the interest of the Internet community early on. Different
approaches have been proposed to classify Internet traffic to manage both security and …

Semi-supervised encrypted traffic classification with deep convolutional generative adversarial networks

AS Iliyasu, H Deng - Ieee Access, 2019 - ieeexplore.ieee.org
Network traffic classification serves as a building block for important tasks such as security
and quality of service management. The field has been studied for a long time, with many …

HEDGE: efficient traffic classification of encrypted and compressed packets

F Casino, KKR Choo, C Patsakis - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
As the size and source of network traffic increase, so does the challenge of monitoring and
analyzing network traffic. Therefore, sampling algorithms are often used to alleviate these …

The next generation cognitive security operations center: network flow forensics using cybersecurity intelligence

K Demertzis, P Kikiras, N Tziritas, SL Sanchez… - Big data and cognitive …, 2018 - mdpi.com
A Security Operations Center (SOC) can be defined as an organized and highly skilled team
that uses advanced computer forensics tools to prevent, detect and respond to cybersecurity …

The next generation cognitive security operations center: adaptive analytic lambda architecture for efficient defense against adversarial attacks

K Demertzis, N Tziritas, P Kikiras, SL Sanchez… - Big Data and Cognitive …, 2019 - mdpi.com
A Security Operations Center (SOC) is a central technical level unit responsible for
monitoring, analyzing, assessing, and defending an organization's security posture on an …

Practical evaluation of encrypted traffic classification based on a combined method of entropy estimation and neural networks

K Zhou, W Wang, C Wu, T Hu - Etri Journal, 2020 - Wiley Online Library
Encrypted traffic classification plays a vital role in cybersecurity as network traffic encryption
becomes prevalent. First, we briefly introduce three traffic encryption mechanisms: IPsec …

Feature engineering and ensemble learning-based classification of VPN and non-VPN-based network traffic over temporal features

G Abbas, U Farooq, P Singh, SS Khurana… - SN Computer Science, 2023 - Springer
With the rapid advancement in technology, the constant emergence of new applications and
services has resulted in a drastic increase in Internet traffic, making it increasingly …