The Industrial Internet of Things (IIoT) ecosystem faces increased risks and vulnerabilities
due to adopting Industry 4.0 standards. Integrating data from various places and converging …

The Industrial Internet of Things (IIoT) is a collection of interconnected smart sensors and
actuators with industrial software tools and applications. IIoT aims to enhance manufacturing …

Anomaly-based intrusion detection systems identify the computer network behavior which
deviates from the statistical model of typical network behavior. Binary classifiers based on …

Detecting malicious attacks in Industrial Internet of Things (IIoT) is crucial to minimize
downtime and financial losses. However, existing deep learning (DL) research faces …

Introducing IoT devices to healthcare fields has made it possible to remotely monitor
patients' information and provide a proper diagnosis as needed, resulting in the Internet of …

With the evolving sophisticated attack techniques and cyber-attacks, businesses must adapt
their threat detection and response mechanisms. It is paramount to explorecontemporary …

The rapid growth of the Internet of Things (IoT) in the industrial sector has given rise to a new
term: the Industrial Internet of Things (IIoT). The IIoT is a collection of devices, apps, and …

The Internet of Medical Things (IoMT) has been integrated and deployed in the health care
domain as it significantly facilitates medical services for both health care providers and …

Unsupervised anomaly detection (AD) methods, either reconstruction based or prediction
based, determine anomalies based on residuals. Occasional mutations in a single variable …

The traditional Transformer model primarily employs a self-attention mechanism to capture
global feature relationships, potentially overlooking local relationships within sequences …