HLMCC: A Hybrid Learning Anomaly Detection Model for Unlabeled Data in Internet of Things

HLMCC: A Hybrid Learning Anomaly Detection Model for Unlabeled Data in Internet of Things

The Internet of Things (IoT) is a network of distributed devices or sensors connected through the internet to allow gathering and sharing of data. The data generated by these devices is affected by anomalies or abnormal behaviour due to attack issues, or breakdown in devices, as examples. However, m...

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Bibliographic Details
Main Authors: Nusaybah Alghanmi, Reem Alotaibi, Seyed M Buhari
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Anomaly detection
Internet of Things
machine learning
unlabelled data
sensor data
Online Access:https://ieeexplore.ieee.org/document/8932357/

Internet

https://ieeexplore.ieee.org/document/8932357/

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