Bigdata and IoT technologies are developing rapidly. Accordingly, consideration of network
security is also emphasized, and efficient intrusion detection technology is required for …

Network anomaly detection it is a major concern and challenging area nowadays although it
provides effective and efficient mechanism from different types of attack. To enhance the …

For traditional network anomaly detection system, the detection performance is related to the
selected features and training dataset. But traditional methods adopt handcraft feature …

Network traffic anomaly detection is an important technique of ensuring network security.
However, there are usually three problems with existing machine learning based anomaly …

Network anomaly detection plays a crucial role as it provides an effective mechanism to
block or stop cyberattacks. With the recent advancement of Artificial Intelligence (AI), there …

Abstract Network Anomaly Detection is still an open challenging task that aims to detect
anomalous network traffic for security purposes. Usually, the network traffic data are large …

To improve the accuracy and real-time performance of anomaly detection models in
complex network environments, a network anomaly detection model based on random forest …

Machine learning based network anomaly detection methods, which are already effective
defense mechanisms against known network intrusion attacks, have also proven themselves …

Network traffic anomaly detection is a key step in identifying and preventing network security
threats. This study aims to construct a new deep-learning-based traffic anomaly detection …

As the number of heterogenous IP-connected devices and traffic volume increase, so does
the potential for security breaches. The undetected exploitation of these breaches can bring …