The advancement of 5G technology has enabled the IIoT (Industrial Internet of Things) to
integrate artificial intelligence, cloud computing, and edge computing in real-time, leading to …

Adaptive online machine learning using data streams is an emerging research area in which
algorithms learn dynamically from live data and update regularly for future predictions. On …

This research project aims to increase the employees' cybersecurity awareness by
proposing a training program that consists of pre-game and post-game phishing attacks, pre …

A network intrusion detection method for information systems using federated learning and
improved transformer is proposed to address the problems of long detection time and low …

The number of cyberattacks has grown along with the expansion of the Internet of Things
(IoT), which necessitates detection of cyberattacks on IoT devices. Different machine …

This paper presents an intrusion detection system (IDS) leveraging a hybrid machine
learning approach aimed at enhancing the security of IoT devices at the edge, specifically …

The implementation of secure communication in the Industrial Internet of Things (IIoT) has
made and it is a significant security concern. Identity-based generalized signcryption …

Agricultural monitoring is pivotal for optimizing crop yields and farm productivity, yet
traditional systems face drawbacks such as limited coverage and inefficient resource …

The immense growth of the Internet of Things (IoT) technology enables potential intruders
easy access to the IoT data. The Anomaly Detection System (ADS) detects abnormal …

Fog computing provides maximum flexibility and low latency by divesting the usage of cloud
resources and amenities to the end users. In rendering the services to the cloud …