An Unsupervised Machine Learning Algorithm for Attack and Anomaly Detection in IoT Sensors

The development of IoT-based sensor systems, such as many control systems in industries, is essential, and sensors are essential for detecting chemical and biological threats, monitoring the environment, and implementing intelligent home automation. Data from Wireless SensorNetwork is retrieved via...

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Vydáno v:	Wireless personal communications Ročník 144; číslo 1-2; s. 1 - 25
Hlavní autor:	Alangari, Someah
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.09.2025 Springer Nature B.V
Témata:	Algorithms Anomalies Big Data Biomonitoring Blockchain Business metrics Cluster analysis Clustering Communications Engineering Computer Communication Networks Cybersecurity Engineering Filtration Internet of Things Machine learning Mobile ad hoc networks Network reliability Networks Optimization Optimization techniques Routing (telecommunications) Sensors Signal,Image and Speech Processing Statistical analysis Time series Unsupervised learning Machine learning (ML) Internet of Things (IoT) Advanced hybridized genetic style and fire fly algorithm (AHGFFA) Security monitors (SMs)
ISSN:	0929-6212, 1572-834X
On-line přístup:	Získat plný text
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