Anomaly detection in network traffic, both in general computer networks and specifically in
Internet of Things (IoT) networks, plays a crucial role in ensuring computer network security …

With the increasing adoption of Internet of Things (IoT), research into anomaly detection
(AD) in IoT network traffic is gaining importance. Malicious disturbances (eg malware and …

Anomaly detection plays a critical role in maintaining the security and integrity of network
systems. This paper conducts a comparative study of deep learning approaches for anomaly …

The rapid proliferation of Internet of Things (IoT) devices has revolutionized various
domains, introducing unprecedented convenience and efficiency. However, this expansion …

Widespread adoption of Internet of Things (IoT) devices increased the variety of devices
connected to a network. These devices have become a primary target of cyber-attacks as …

Due to their versatility and effectiveness, Deep Learning (DL) approaches are increasingly
used in designing Network Intrusion Detection Systems (NIDSs). Specifically, Anomaly …

Deep learning-based traffic anomaly detection methods are usually fed with high-
dimensional statistical features. The greatest challenges are how to detect complex inter …

Due to the advance in network technologies, the number of network users is growing rapidly,
which leads to the generation of large network traffic data. This large network traffic data is …

Network operators need effective tools to quickly detect anomalies in traffic data for
identifying network attacks. In contrast to traditional Internet, anomaly detection in IoT …

The largest problems facing any corporation today, as well as network administrators, are
network abnormalities. Numerous strategies have been used and put into practice to stop …