On detecting and identifying faulty internet of things devices and outages
Feng Wang, Eduard Babulak, Yongning Tang
Abstract
As internet of things (IoT) devices play an integral role in our everyday life, it is critical to monitor the health of the IoT devices. However, fault detection in IoT is much more challenging compared with that in traditional wired networks. Traditional observing and polling are not appropriate for detecting faults in resource-constrained IoT devices. Because of the dynamic feature of IoT devices, these detection methods are inadequate for IoT fault detection. In this paper, we propose two methods that can monitor the health status of IoT devices through monitoring the network traffic of these devices. Based on the collected traffic or flow entropy, these methods can determine the health status of IoT devices by comparing captured traffic behavior with normal traffic patterns. Our measurements show that the two methods can effectively detect and identify malfunctioned or defective IoT devices.
Keywords
Entropy; Fault detection; IoT; IoT outages; Traffic deviation;
DOI:
https://doi.org/10.11591/eei.v10i6.2698
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Bulletin of EEI Stats
Bulletin of Electrical Engineering and Informatics (BEEI) ISSN: 2089-3191, e-ISSN: 2302-9285 This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU) .