Network anomalies, circumstances in which the network behavior deviates from its normal
operational baseline, can be due to various factors such as network overload conditions …

This research introduces a theoretical framework for network anomaly detection in
cybersecurity, emphasizing the integration of adaptive machine learning models, ensemble …

Abstract Despite a Network Anomaly Detection System (NADS) being capable of detecting
existing and zero-day attacks, it is still not universally implemented in industry and real …

With the development of new technologies such as big data, cloud computing, and the
Internet of Things, network attack technology is constantly evolving and upgrading, and …

Anomaly detection aims to discover patterns in data that do not conform to the expected
normal behaviour. One of the significant issues for anomaly detection techniques is the …

We evaluate methods for applying unsupervised anomaly detection to cybersecurity
applications on computer network traffic data, or flow. We borrow from the natural language …

Anomaly detection systems can accurately identify malicious network traffic, providing
network security. With the development of internet technology, network attacks are becoming …

Anomaly detection in communication networks is the first step in the challenging task of
securing a network, as anomalies may indicate suspicious behaviors, attacks, network …

This paper looks into the problem of detecting network anomalies by analyzing NetFlow
records. While many previous works have used statistical models and machine learning …

The Internet and computer networks are currently suffering from different security threats.
This paper presents a new method called AMF-LSTM for abnormal traffic detection by using …