Deep Learning Anomaly Detection for Cellular IoT With Applications in Smart Logistics

Deep Learning Anomaly Detection for Cellular IoT With Applications in Smart Logistics

The number of connected Internet of Things (IoT) devices within cyber-physical infrastructure systems grows at an increasing rate. This poses significant device management and security challenges to current IoT networks. Among several approaches to cope with these challenges, data-based methods root...

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Bibliographic Details
Main Authors: Milos Savic, Milan Lukic, Dragan Danilovic, Zarko Bodroski, Dragana Bajovic, Ivan Mezei, Dejan Vukobratovic, Srdjan Skrbic, Dusan Jakovetic
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Anomaly detection
cellular IoT
industrial IoT
machine learning
smart logistics
Online Access:https://ieeexplore.ieee.org/document/9402912/

Internet

https://ieeexplore.ieee.org/document/9402912/

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