The exponential growth of the internet and inter-connectivity has resulted in an extensive
increase in network size and the corresponding data, which has led to numerous novel …

Adapting modern approaches for network intrusion detection is becoming critical, given the
rapid technological advancement and adversarial attack rates. Therefore, packet-based …

As a security defense technique to protect networks from attacks, a network intrusion
detection model plays a crucial role in the security of computer systems and networks …

Machine learning (ML) and deep learning (DL) advancements have greatly enhanced
anomaly detection of network intrusion detection systems (NIDS) by empowering them to …

Network-based intrusion detection (N-IDS) is an essential system inside an organization in a
smart healthcare enterprise system to prevent the system and its networks from network …

Current flow-based Network Intrusion Detection Systems (NIDSs) have the drawback of
detecting attacks only once the flow has ended, resulting in potential delays in attack …

Deep Learning (DL) based methods have shown great promise in network intrusion
detection by identifying malicious network traffic behavior patterns with high accuracy, but …

Using traditional methods based on detection rules written by human security experts
presents significant challenges for the accurate detection of network threats, which are …

Botnets are computer networks controlled by malicious actors that present significant
cybersecurity challenges. They autonomously infect, propagate, and coordinate to conduct …

Network intrusion detection technology has always been an indispensable protection
mechanism for industrial network security. The rise of new forms of network attacks has …