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A comprehensive survey on network anomaly detection
Nowadays, there is a huge and growing concern about security in information and
communication technology among the scientific community because any attack or anomaly …
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 …
networks. Flow-based intrusion detection only inspects the packet header and does not …
Anomaly-based intrusion detection from network flow features using variational autoencoder
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 …
intrusion detection systems processing a small amount of traffic data. Furthermore, anomaly …
Deep learning approach for network intrusion detection in software defined networking
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 …
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
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 …
convenient services in intelligent transportation systems, and yet vulnerable to various …
A survey of network flow applications
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 …
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
With the increasing rates of interconnected Internet of Things (IoT) devices within software-
defined networking (SDN) environments, Distributed Denial-of-Service (DDoS) attacks have …
defined networking (SDN) environments, Distributed Denial-of-Service (DDoS) attacks have …
[HTML][HTML] DeepIDS: Deep learning approach for intrusion detection in software defined networking
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 …
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
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 …
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 …
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 …
(SDN), which makes it possible to control the network from a central location and provides …