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 …
anomalies, and misconfigurations, among others things, in Internet traffic. In particular, traffic …
From intrusion detection to attacker attribution: A comprehensive survey of unsupervised methods
Over the last five years there has been an increase in the frequency and diversity of network
attacks. This holds true, as more and more organizations admit compromises on a daily …
attacks. This holds true, as more and more organizations admit compromises on a daily …
A survey of clustering algorithms for big data: Taxonomy and empirical analysis
Clustering algorithms have emerged as an alternative powerful meta-learning tool to
accurately analyze the massive volume of data generated by modern applications. In …
accurately analyze the massive volume of data generated by modern applications. In …
FlowPic: A generic representation for encrypted traffic classification and applications identification
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 …
as, traffic engineering, or to detect and prevent application or application types that violate …
[HTML][HTML] Network traffic classification for data fusion: A survey
Traffic classification groups similar or related traffic data, which is one main stream
technique of data fusion in the field of network management and security. With the rapid …
technique of data fusion in the field of network management and security. With the rapid …
Recent advances and emerging challenges of feature selection in the context of big data
V Bolón-Canedo, N Sánchez-Maroño… - Knowledge-based …, 2015 - Elsevier
In an era of growing data complexity and volume and the advent of big data, feature
selection has a key role to play in helping reduce high-dimensionality in machine learning …
selection has a key role to play in helping reduce high-dimensionality in machine learning …
TSCRNN: A novel classification scheme of encrypted traffic based on flow spatiotemporal features for efficient management of IIoT
Abstract In the Industrial Internet of Things (IIoT) in the 5G era, the growth of smart devices
will generate a large amount of data traffic, bringing a huge challenge of network traffic …
will generate a large amount of data traffic, bringing a huge challenge of network traffic …
Flowpic: Encrypted internet traffic classification is as easy as image recognition
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 …
become harder in recent years due to the use of encryption, eg, by VPN and Tor. Current …
A whale optimization algorithm-trained artificial neural network for smart grid cyber intrusion detection
L Haghnegahdar, Y Wang - Neural computing and applications, 2020 - Springer
The smart grid is a revolutionary, intelligent, next-generation power system. Due to its cyber
infrastructure nature, it must be able to accurately and detect potential cyber-attacks and …
infrastructure nature, it must be able to accurately and detect potential cyber-attacks and …
Feature analysis for machine learning-based IoT intrusion detection
Internet of Things (IoT) networks have become an increasingly attractive target of
cyberattacks. Powerful Machine Learning (ML) models have recently been adopted to …
cyberattacks. Powerful Machine Learning (ML) models have recently been adopted to …