… Using artificial neural network (ANN)-based intrusion detection is promising for … of learning
from actual examples. In this paper, a developed learning model for fast learning network (FLN…

… According to our studies, this is the first paper aimed to explore intrusion detection schemes
that use deep learning networks. The contribution of this survey article can be listed as …

… network (WSN), internet of things (IoT), cloud computing, etc. We then redefined our keyword
as intrusion detection system, network anomaly detection, … a Fast Learning Network (FLN). …

… NIDS—namely, on-the-move Intrusion Detection System (OMIDS)—to categorise these …
intrusion detection model for IVNs, based on the VGG16 classifier deep learning model, to learn …

… deep learning approach for network traffic identification in [17]. The authors performed TCP
based unknown protocols identification in their work instead of network intrusion detection. …

… current studies of intrusion detection by machine learning techniques. … machine learning
techniques used in the intrusion detection … intrusion detection systems using machine learning …

… detection accuracy. This paper presents a novel deep learning technique for intrusion detection…
(NDAE) for unsupervised feature learning. Furthermore, we also propose our novel deep …

… This paper presents a novel approach for detecting network intrusions based on a competitive
learning neural network. In the … The improved competitive learning network (ICLN) can …

… is a deep neural network classifier of a combination of multilayer unsupervised learning
networks, which is called as Restricted Boltzmann Machine, and a supervised learning network, …

… attacks in the network. In our study, we explore how to model an intrusion detection system
based on deep learning, and we propose a deep learning approach for intrusion detection …