139943 - A practical model based on anomaly detection for protecting medical IoT control services against external attacks.pdf (3.39 MB)
A practical model based on anomaly detection for protecting medical IoT control services against external attacks
journal contributionposted on 2023-05-20, 16:10 authored by Fang, L, Li, Y, Liu, Z, Yin, C, Li, M, Cao, Z
The application of the Internet of Things (IoT) in medical field has brought unprecedented convenience to human beings. However, attackers can use device configuration vulnerabilities to hijack devices, control services, steal medical data, or make devices operate illegally. These restrictions have led to huge security risks for IoT, and have challenged the management of critical infrastructure services. Based on these problems, this article proposes an anomaly detection system for detecting illegal behavior (DIB) in medical IoT environment.The DIB system can analyze data packets transmitted by medical IoT devices, learn operation rules by itself, and remind management personnel that the device is in an abnormal operation state to ensure the safety of control service. We further propose a model that is based on rough set theory and fuzzy core vector machine (FCVM) to improve the accuracy of DIB classification anomalies. Experimental results show that the R-FCVM is effective.
Publication titleIEEE Transactions on Industrial Informatics
Pagination4260 - 4269
Department/SchoolSchool of Information and Communication Technology
PublisherInstitute of Electrical and Electronics Engineers
Place of publicationUnited States
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