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Anomaly Detection for Wireless Communication Links via Data Integrity Modeling

conference contribution
posted on 2022-10-04, 03:42 authored by Mahyar Nemati, Jihong ParkJihong Park, M Jeon, Jinho ChoiJinho Choi
Wireless connectivity plays a crucial role in col-lecting data from a large number of devices and sensors for various Internet-of-Things (IoT) applications including supply chain management and personalized healthcare. In most IoT applications, for various reasons, a collected data set may include incorrect or corrupted data samples, which should be detected and removed. For example, malicious devices may send fake information or malfunctioned remote devices can respond improperly. In this paper, we study anomaly detection for wireless links, not data sets sent by devices, to see any anomalies in the physical and link layers associated with connected devices to a network. The resulting approach can be viewed as preemptive anomaly detection and be part of causal anomaly discovery that helps determine whether anomalies detected in a data set are caused by errors in wireless links or transceivers.

History

Pagination

1756 - 1761

ISBN-13

9789881476890

Title of proceedings

2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021 - Proceedings

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