The obtained results demonstrate that simple and broad scope classifiers, using features that consume little resources, can be developed to detect such faults.
This paper injected and subsequently proceeded to detect representative firmware and hardware anomalies that can be used by attackers to cause major losses ...
We evaluated the performance of several machine learning techniques commonly used to detect anomalies (i.e. OCSVM, kNN, AutoEnconder), in order to determine if ...
Security and Fault Detection in In-node components of IIoT Constrained Devices. October 2019. DOI:10.1109/LCN44214.2019.8990697. Conference: Local Computer ...
In this section, we will briefly overview the techniques for monitoring the hardware and firmware of constrained devices, and will identify the main post- ...
We propose an approach to detect and classify faults that are typical in these devices, based on machine learning techniques that use energy, processing, and ...
Security and fault detection in in-node components of IIoT constrained devices. D Raposo, A Rodrigues, S Sinche, JS Silva, F Boavida. 2019 IEEE 44th ...
Security and fault detection in in-node components of IIoT constrained devices. D Raposo, A Rodrigues, S Sinche, JS Silva, F Boavida. 2019 IEEE 44th ...
In this paper, we propose an intrusion detection framework for the energy-constrained IoT devices which form the foundation of an IIoT ecosystem.
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Raposo, Security and fault detection in in-node components of iIoT constrained devices, с. 282; Hu, 5G-enabled fault detection and diagnostics: How do we ...