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 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 …

FlowPic: A generic representation for encrypted traffic classification and applications identification

T Shapira, Y Shavitt - IEEE Transactions on Network and …, 2021 - ieeexplore.ieee.org
Identifying the type of a network flow or a specific application has many advantages, such
as, traffic engineering, or to detect and prevent application or application types that violate …

Network intrusion detection: Based on deep hierarchical network and original flow data

Y Zhang, X Chen, L **, X Wang, D Guo - IEEE Access, 2019 - ieeexplore.ieee.org
Network intrusion detection plays a very important role in protecting computer network
security. The abnormal traffic detection and analysis by extracting the statistical features of …

Flowpic: Encrypted internet traffic classification is as easy as image recognition

T Shapira, Y Shavitt - IEEE INFOCOM 2019-IEEE conference …, 2019 - ieeexplore.ieee.org
Identifying the type of a network flow or a specific application has many advantages, but
become harder in recent years due to the use of encryption, eg, by VPN and Tor. Current …

A fused CNN model for WBC detection with MRMR feature selection and extreme learning machine

F Özyurt - Soft Computing, 2020 - Springer
White blood cell (WBC) test is used to diagnose many diseases, particularly infections,
ranging from allergies to leukemia. A physician needs clinical experience to detect and …

A novel network intrusion detection system based on CNN

L Chen, X Kuang, A Xu, S Suo… - 2020 eighth international …, 2020 - ieeexplore.ieee.org
Network intrusion detection system (NIDS) plays an important role in network security. It can
detect the malicious traffic and prevent the network intrusion. Traditional methods used …

Ggfast: Automating generation of flexible network traffic classifiers

J Piet, D Nwoji, V Paxson - Proceedings of the ACM SIGCOMM 2023 …, 2023 - dl.acm.org
When employing supervised machine learning to analyze network traffic, the heart of the
task often lies in develo** effective features for the ML to leverage. We develop GGFAST …

A new technique for ECG signal classification genetic algorithm Wavelet Kernel extreme learning machine

A Diker, D Avci, E Avci, M Gedikpinar - Optik, 2019 - Elsevier
The examination and classification of Electrocardiogram (ECG) records have become
particularly significant for diagnosing heart diseases. Machine learning methods are widely …

ECG signal classification and arrhythmia detection using ELM-RNN

S Kuila, N Dhanda, S Joardar - Multimedia Tools and Applications, 2022 - Springer
Arrhythmia is a unique type of heart disease which produces inefficient and irregular
heartbeat. This is a cardiac disease which is diagnosed through electrocardiogram (ECG) …