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 …

The emergence and continued reliance on the Internet and related technologies has
resulted in the generation of large amounts of data that can be made available for analyses …

Cyber-security garnered significant attention due to the increased dependency of individuals
and organizations on the Internet and their concern about the security and privacy of their …

High-speed networks are becoming common nowadays. Naturally, a challenge that arises is
that the intrusion detection system (IDS) should timely detect attacks in huge volumes of …

A pattern matching method (signature-based) is widely used in basic network intrusion
detection systems (IDS). A more robust method is to use a machine learning classifier to …

The use of autonomous vehicles (AVs) is a promising technology in Intelligent
Transportation Systems (ITSs) to improve safety and driving efficiency. Vehicle-to-everything …

With the wide spread of sensors and smart devices in recent years, the data generation
speed of the Internet of Things (IoT) systems has increased dramatically. In IoT systems …

Deep learning has become a research hotspot in the field of network intrusion detection. In
order to further improve the detection accuracy and performance, we proposed an intrusion …

With a plethora of new connections, features, and services introduced, the 5th generation
(5G) wireless technology reflects the development of mobile communication networks and is …

Presently, we are living in a hyper-connected world where millions of heterogeneous
devices are continuously sharing information in different application contexts for wellness …