Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

''Knowledge is power” is an old adage that has been found to be true in today's information
age. Knowledge is derived from having access to information. The ability to gather …

Recently, due to the rapid development and remarkable result of deep learning (DL) and
machine learning (ML) approaches in various domains for several long-standing artificial …

Cyber-attacks was organized in a simple and random way in the past. However attacks are
carried out systematically and long term nowadays. In addition, the high calculation volume …

Edge computing has emerged as a transformative data processing method by decentralizing
computations and bringing them toward the data source, significantly reducing latency and …

We investigate how human beliefs are associated with the absorption of specialist
knowledge that is required to produce cyber-security. We ground our theorizing in the …

Data Stream Machine Learning is rapidly gaining popularity within the network monitoring
community as the big data produced by network devices and end-user terminals goes …

With the ever-growing occurrence of networking attacks, robust network security systems are
essential to prevent and mitigate their harming effects. In recent years, machine learning …

Cybersecurity ventures expect that cyber-attack damage costs will rise to $11.5 billion in
2019 and that a business will fall victim to a cyber-attack every 14 seconds. Notice here that …

Anomaly (outlier) detection is one of the most important problems of modern data analysis.
Anomalies can be the results of database users' mistakes, operational errors or just missing …