Global networking, growing computer infrastructure complexity and the ongoing migration of
many private and business aspects to the electronic domain commonly mandate using …

Multiple datasets have been proposed to create Machine Learning (ML)-based Network
Intrusion Detection Systems (NIDS). However, many of these datasets suffer from sub …

With the usage of Machine Learning (ML) algorithms in modern-day Network Intrusion
Detection Systems (NIDS), contemporary network communications are efficiently protected …

As software-defined network (SDN) adoption increases, it becomes increasingly important to
develop effective solutions to defend them against cyber attacks. A prominent cyberattack …

Interdisciplinary developments like the Smart Grid (SG) provide enhanced functionality like
efficient power delivery, reliability, and safety while ensuring the smooth integration of …

Machine learning (ML)-based network intrusion detection systems (NIDS) have become a
prospective approach to efficiently protect network communications. However, ML models …

Software-defined networking (SDN) have emerged as a popular approach to manage
network traffic in data centers. By separating the control plane from the data plane, SDN …

Microgrids have revolutionized the field of power systems as they provide higher reliability
and power quality over traditional power systems by possessing the ability to self-supply …

Vehicular Ad-Hoc Networks (VANETs) have become an integral component of contemporary
vehicular technology. This technology provides advanced features like traffic and weather …

Machine learning (ML)-based network intrusion detection systems (NIDS) have become a
contemporary approach to efficiently protect network communications from cyber attacks …