A comprehensive survey on network anomaly detection

G Fernandes, JJPC Rodrigues, LF Carvalho… - Telecommunication …, 2019 - Springer
Nowadays, there is a huge and growing concern about security in information and
communication technology among the scientific community because any attack or anomaly …

Flow-based intrusion detection: Techniques and challenges

MF Umer, M Sher, Y Bi - Computers & Security, 2017 - Elsevier
Flow-based intrusion detection is an innovative way of detecting intrusions in high-speed
networks. Flow-based intrusion detection only inspects the packet header and does not …

Anomaly-based intrusion detection from network flow features using variational autoencoder

S Zavrak, M Iskefiyeli - IEEe Access, 2020 - ieeexplore.ieee.org
The rapid increase in network traffic has recently led to the importance of flow-based
intrusion detection systems processing a small amount of traffic data. Furthermore, anomaly …

Deep learning approach for network intrusion detection in software defined networking

TA Tang, L Mhamdi, D McLernon… - … on wireless networks …, 2016 - ieeexplore.ieee.org
Software Defined Networking (SDN) has recently emerged to become one of the promising
solutions for the future Internet. With the logical centralization of controllers and a global …

Collaborative intrusion detection for VANETs: A deep learning-based distributed SDN approach

J Shu, L Zhou, W Zhang, X Du… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Vehicular Ad hoc Network (VANET) is an enabling technology to provide a variety of
convenient services in intelligent transportation systems, and yet vulnerable to various …

A survey of network flow applications

B Li, J Springer, G Bebis, MH Gunes - Journal of Network and Computer …, 2013 - Elsevier
It has been over 16 years since Cisco's NetFlow was patented in 1996. Extensive research
has been conducted since then and many applications have been developed. In this survey …

Multi-level deep neural network for distributed denial-of-service attack detection and classification in software-defined networking supported internet of things networks

YA Abid, J Wu, G Xu, S Fu… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
With the increasing rates of interconnected Internet of Things (IoT) devices within software-
defined networking (SDN) environments, Distributed Denial-of-Service (DDoS) attacks have …

[HTML][HTML] DeepIDS: Deep learning approach for intrusion detection in software defined networking

TA Tang, L Mhamdi, D McLernon, SAR Zaidi… - Electronics, 2020 - mdpi.com
Software Defined Networking (SDN) is develo** as a new solution for the development
and innovation of the Internet. SDN is expected to be the ideal future for the Internet, since it …

A survey of deep learning techniques for cybersecurity in mobile networks

E Rodriguez, B Otero, N Gutierrez… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The widespread use of mobile devices, as well as the increasing popularity of mobile
services has raised serious cybersecurity challenges. In the last years, the number of …

[HTML][HTML] Network threat detection using machine/deep learning in sdn-based platforms: a comprehensive analysis of state-of-the-art solutions, discussion, challenges …

N Ahmed, A Ngadi, JM Sharif, S Hussain, M Uddin… - Sensors, 2022 - mdpi.com
A revolution in network technology has been ushered in by software defined networking
(SDN), which makes it possible to control the network from a central location and provides …