This study summarizes major literature reviews on machine learning systems for network
analysis and intrusion detection. Furthermore, it provides a brief lesson description of each …

Rapid developments in network technologies and the amount and scope of data transferred
on networks are increasing day by day. Depending on this situation, the density and …

Аннотация This article delves into the application of machine learning techniques in
network security for proactive threat detection. It explores how artificial intelligence …

With the proliferation of internet users around the world, it is becoming imperative to make
communications safer than before. A network intrusion detection system is pivotal for …

Security has been a crucial factor in this modern digital period due to the rapid development
of information technology, which is followed by serious computer crimes that, in turn, led to …

Cyber threats and data breaches have become more sophisticated and stealthier over time.
Traditional rule-based intrusion detection systems fail to detect many modern attacks. This …

In this review, significant literature surveys on machine learning (ML) and deep learning
(DL) techniques for network analysis of intrusion detection are explained. In addition, it …

A popular approach for detecting network intrusion attempts is to monitor the network traffic
for anomalies. Extensive research effort has been invested in anomaly-based network …

This paper discusses the application and advantages of machine learning in anomaly
detection of network security traffic. By summarizing the existing methods and techniques of …

Traffic analysis has many purposes such as evaluating the performance and security of
network operations and management. Therefore, network traffic analysis is considered vital …