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An OMNeT++-Based Approach to Narrowband-IoT Traffic Generat..:
, In:
2023 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)
,
Darius, Paul
;
Rangelov, Denis
;
Lammel, Philipp
. - p. 286-292 , 2023
Link:
https://doi.org/10.1109/IoTaIS60147.2023.10346041
RT T1 <cTitle>2023 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)</cTitle>: T1 <Title>An OMNeT++-Based Approach to Narrowband-IoT Traffic Generation for Machine Learning-Based Anomaly Detection</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10346041&Exemplar=1&LAN=DE A1 Darius, Paul A1 Rangelov, Denis A1 Lammel, Philipp A1 Tcholtchev, Nikolay YR 2023 SN 2832-1383 K1 Temperature sensors K1 Training K1 Temperature distribution K1 Neural networks K1 Telecommunication traffic K1 Computer architecture K1 Sensors K1 Internet of Things K1 IoT security K1 Smart City K1 Simulation frameworks K1 OMNeT++ K1 Anomaly Detection K1 Data generation K1 Synthetic datasets K1 Machine Learning K1 deep IDS SP 286 OP 292 LK http://dx.doi.org/https://doi.org/10.1109/IoTaIS60147.2023.10346041 DO https://doi.org/10.1109/IoTaIS60147.2023.10346041 SF ELIB - SuUB Bremen
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