Digital Twin is a contemporary digital representation paradigm that is capable of
encompassing the complex interactions within the natural environment. By building …

One of the biggest global challenges for our societies is to provide natural resources to the
rapidly expanding population while maintaining sustainable and ecologically friendly …

Anomaly detection is critical to ensure the security of cyber-physical systems (CPS).
However, due to the increasing complexity of attacks and CPS themselves, anomaly …

Since diverse noises and irregularities impact on sensor data, self-declaration of sensor
data reliability is crucial for advancing Internet of Things applications and industrial …

Internet of Things (IoT) applications relies on sensors to understand and control physical
environments. Sensors are subject to numerous potential faults and sources of inaccuracy …

Due to the nature of Wireless Sensor Networks (WSN), several factors can interfere with
sampling and communication. These faults may compromise data quality and disrupt timing …

In this paper, we use multivariate machine learning-based predictors to replace missing data
and propose a mechanism to evaluate and track correctness by estimating its confidence …

This work addresses the use of a machine-learning based confidence attribution scheme to
detect GPS spoofing attacks against cyber-physical systems. The confidence attribution …

This paper addresses the problem of reducing Wind Turbines Power Curve modeling error
and false-positive classifications of incoming wind speed and respective power generation …

Cyber-Physical Systems (CPS) rely on sensing to control and optimize their operation.
Nevertheless, sensing itself is prone to errors that can originate at several stages, from …