[HTML][HTML] Deep learning for network traffic monitoring and analysis (NTMA): A survey
Modern communication systems and networks, eg, Internet of Things (IoT) and cellular
networks, generate a massive and heterogeneous amount of traffic data. In such networks …
networks, generate a massive and heterogeneous amount of traffic data. In such networks …
[HTML][HTML] Using a vae-som architecture for anomaly detection of flexible sensors in limb prosthesis
Flexible wearable sensor electronics, combined with advanced software functions, pave the
way toward increasingly intelligent healthcare devices. One important application area is …
way toward increasingly intelligent healthcare devices. One important application area is …
[HTML][HTML] A combined strategy for dynamic probabilistic risk assessment of fission battery designs using EMRALD and DEPM
A Earthperson, CM Otani, D Nevius, SR Prescott… - Progress in Nuclear …, 2023 - Elsevier
The notion of nuclear reactors with battery-like capabilities, called fission batteries, puts forth
system requirements and design constraints that have so far been unseen in the nuclear …
system requirements and design constraints that have so far been unseen in the nuclear …
A hybrid behavior-and Bayesian network-based framework for cyber–physical anomaly detection
In recent years, the increasing Internet connectivity and heterogeneity of industrial protocols
have been raising the number and nature of cyber-attacks against Industrial Control …
have been raising the number and nature of cyber-attacks against Industrial Control …
[PDF][PDF] Model-based fault injection experiments for the safety analysis of exoskeleton system
Model-based fault injection methods are widely used for the evaluation of fault tolerance in
safety-critical control systems. In this paper, we introduce a new model-based fault injection …
safety-critical control systems. In this paper, we introduce a new model-based fault injection …
Process mining for digital twin development of industrial cyber-physical systems
Digital twin development of industrial cyber-physical systems requires modeling, simulation,
and monitoring to provide accurate digital replicas mimicking system dynamics. To this aim …
and monitoring to provide accurate digital replicas mimicking system dynamics. To this aim …
Evaluating virtualization for fog monitoring of real-time applications in mixed-criticality systems
Technological advances in embedded systems and the advent of fog computing led to
improved quality of service of applications of cyber-physical systems. In fact, the deployment …
improved quality of service of applications of cyber-physical systems. In fact, the deployment …
[HTML][HTML] A Process Mining-based unsupervised Anomaly Detection technique for the Industrial Internet of Things
Abstract Industrial Internet of Things (IIoT) applications in Industry 4.0 collect and process
Time Series (TS) originating from heterogeneous sources. Many data-driven techniques …
Time Series (TS) originating from heterogeneous sources. Many data-driven techniques …
Using fault injection for the training of functions to detect soft errors of dnns in automotive vehicles
Advanced functions based on Deep Neural Networks (DNN) have been widely used in
automotive vehicles for the perception of operational conditions. To be able to fully exploit …
automotive vehicles for the perception of operational conditions. To be able to fully exploit …
Model-based error detection for industrial automation systems using lstm networks
The increasing complexity of modern automation systems leads to inevitable faults. At the
same time, structural variability and untrivial interaction of the sophisticated components …
same time, structural variability and untrivial interaction of the sophisticated components …