With the continuous increase in cyberattacks over the past few decades, the quest to
develop a comprehensive, robust, and effective intrusion detection system (IDS) in the …

The internet has unlocked a whole new universe. It has no bounds and provides individuals
with tremendous economic prospects all throughout the world. People can live better lives …

For businesses to operate effectively, networks and computer systems have become crucial
instruments. They are now used in all professional fields, including the military, universities …

Machine learning and neural networks have become increasingly popular solutions for
encrypted malware traffic detection. They mine and learn complex traffic patterns, enabling …

The Intrusion Detection System (IDS)-is one that monitors network traffic to issue alerts about
any suspicious activity on the network. Conventionally, there are two types of IDSs-Signature …

Anomaly detection is a longstanding and active research area that has many applications in
domains such as finance, security, and manufacturing. However, the efficiency and …

The objective of this paper is to propose a hybrid model of Network Intrusion Detection
System (NIDS) based on the use of two types of IDS: Signature-based NIDS (SNIDS) and …

Machine learning-based Network Intrusion Detection Systems (NIDS) are designed to
protect networks by identifying anomalous behaviors or improper uses. In recent years …

Nowadays, it became difficult to ensure data security because of the rapid development of
information technology according to the Vs of Big Data. To secure a network against …

In recent years, with the increased usage of the Internet of Things (IoT) devices, cyber-
attacks have become a serious threat over the Internet. These devices have low memory …