Nowadays, the ever-increasing complication and severity of security attacks on computer
networks have inspired security researchers to incorporate different machine learning …

Intrusion detection (ID) is critical in securing computer networks against various malicious
attacks. Recent advancements in machine learning (ML), deep learning (DL), federated …

Developing cyber security is very necessary and has attracted considerable attention from
academy and industry organizations worldwide. It is also very necessary to provide …

This study proposes a novel framework to improve intrusion detection system (IDS)
performance based on the data collected from the Internet of things (IoT) environments. The …

Abstract The Internet of Things (IoT) enabled technology will be adopted to develop smart
cities, electronic commerce, electronic learning, electronic health, and other aspects of …

The great advancements in communication, cloud computing, and the internet of things (IoT)
have opened critical challenges in security. With these developments, cyberattacks are also …

The recent advancements in science, engineering, and technology have facilitated huge
generation of datasets. These huge datasets contain noisy, redundant, and irrelevant …

In advance accurate prediction of wind turbine blade icing fault is of fundamental
importance. Deep learning is the mainstream prediction technique while existing research …

Abstract Software-Defined Networking (SDN) is widely considered as one of the next
generation network architecture. However, SDN faces with a series of issues which restraint …

The feature selection problem is one of the pre-processing mechanisms to find the optimal
subset of features from a dataset. The search space of the problem will exponentially grow …