Identifying Tampered Radio-Frequency Transmissions in LoRa Networks Using Machine Learning

Long-range networks, renowned for their long-range, low-power communication capabilities, form the backbone of many Internet of Things systems, enabling efficient and reliable data transmission. However, detecting tampered frequency signals poses a considerable challenge due to the vulnerability of...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 24; H. 20; S. 6611
Hauptverfasser:	Senol, Nurettin Selcuk, Rasheed, Amar, Baza, Mohamed, Alsabaan, Maazen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 14.10.2024 MDPI
Schlagworte:	Accuracy Algorithms anomaly detection Computer forensics Cybersecurity Data integrity Datasets Forests frequency analysis Geospatial data Internet of Things IoT LoRa Machine learning Methods Principal components analysis Water quality Wireless communications anomaly detection frequency analysis machine learning cybersecurity LoRa IoT
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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