We propose a versatile and fully data-centric methodology towards anomaly detection and
identification in modern industrial Cyber–Physical Systems (CPS). Our motivation behind …

Software performance anomaly detection is a major challenge in complex industrial cyber-
physical systems. The automated comparison of runtime execution metrics to reference ones …

We present how electrical Extra-Functional Behavioural (EFB) metrics can be used in
generating accurate representations of executional units for industrial Cyber-Physical …

The swift embrace of Industry 4.0 paradigms has led to the growing convergence of
Information Technology (IT) networks and Operational Technology (OT) networks …

Despite significant advances made on anomaly detection systems, few reports are found
documenting their practical integration into the industrial realm. Furthermore, the literature …

We propose a novel methodology for real-time monitoring of software running on embedded
processors in cyber-physical systems (CPS). The approach uses real-time monitoring of …

Cyber-Physical Systems (CPS) constitute the operational basis for a number of critical
national infrastructure (CNI) sectors including but not limited to manufacturing, smart …

The modern industrial environment is equipping myriads of smart manufacturing machines
where the state of each device can be monitored continuously. Such monitoring can help …

Recent advances in AIoT technologies have led to an increasing popularity of utilizing
machine learning algorithms to detect operational failures for cyber-physical systems (CPS) …

We propose an anomaly detection framework that generates an anomaly score for the
current observation of a task. The proposed framework can overcome two major problems in …