Cyberattacks against Industrial Control Systems (ICS) can have harmful physical impacts. Investigating such attacks be difficult, as evidence could lost to damage. This is especially true with stealthy ; i.e., that evade detection. In this paper, we aim engineer Forensic Readiness (FR) in safety-critical, geographically distributed ICS, by proactively collecting potential of attacks. The collec...

Stealthy attacks on Industrial Control Systems can cause significant damage while evading detection. In this article, instead of focusing the detection stealthy attacks, we aim to provide early warnings operators, in order avoid physical and preserve advance data that may serve as an evidence d...

Performance monitoring, anomaly detection, and root-cause analysis in complex cyber–physical systems (CPSs) are often highly intractable due to widely diverse operational modes, disparate data types, fault propagation mechanisms. This paper presents a new data-driven framework for analysis, based on spatiotemporal graphical modeling approach built the concept of symbolic dynamics discovering re...

In order to create an evidence-based orthognathic surgery planning protocol, an investigation of two popular model surgery techniques, the Lockwood keyspacer and the Eastman anatomically-orientated system was carried. This determined (a) the accuracy of positioning of the maxillary cast according to the prescribed treatment plan and (b) the relocation of the maxilla after a simulated Le Fort I ...

Abstract Data-driven fault detection techniques have attracted extensive attention in engineering, industry and many other areas recent years. In real applications, the following situation often occurs: data for certain types of faults (unseen faults) are not available to train models that used detection. Such a scenario can occur when collection becomes highly time-consuming or destructive. To...