Feature selection (FS) is one of the important tasks of data preprocessing in data analytics.
The data with a large number of features will affect the computational complexity, increase a …

Network intrusion detection is the process of identifying malicious activity in a network by
analyzing the network traffic behavior. Data mining techniques are widely used in Intrusion …

Intrusion detection systems (IDS) are used in analyzing huge data and diagnose anomaly
traffic such as DDoS attack; thus, an efficient traffic classification method is necessary for the …

Nowadays, with the development of internet technologies service in the world, the intruders
has been increased rapidly. Therefore, the advent of Intrusion Detection System (IDS) in the …

Availability of suitable and validated data is a key issue in multiple domains for
implementing machine learning methods. Higher data dimensionality has adverse effects on …

The emergence of the internet of things (IOT) as a result of the development of the
communications system has made the study of cyber security more important. Day after day …

Network traffic anomaly may indicate a possible intrusion in the network and therefore
anomaly detection is important to detect and prevent the security attacks. The early research …

In recent years, data security in organizational information systems has become a serious
concern. Many attacks are becoming less detectable by firewall and antivirus software. To …

several studies have suggested that by selecting relevant features for intrusion detection
system, it is possible to considerably improve the detection accuracy and performance of the …

Cybersecurity is one of the great challenges of today's world. Rapid technological
development has allowed society to prosper and improve the quality of life and the world is …