ALBA: Novel Anomaly Location-Based Authentication in IoMT Environment Using Unsupervised ML
作者：
Alruwaili F.J.;Mohanty S.P.;Kougianos E.
通讯作者：
Mohanty, S.P.
作者机构：
Department of Computer Science and Engineering, University of North Texas, Denton, United States
Department of Electrical Engineering, University of North Texas, Denton, United States
通讯机构：
Department of Computer Science and Engineering, United States
语种：
英文
关键词：
Cybersecurity,Healthcare Cyber-Physical System (H-CPS),Intelligent Security,Internet of Medical Things (IoMT),Location-Based Authentication
期刊：
IFIP Advances in Information and Communication Technology
ISSN：
1868-422X
年：
2024
卷：
683 AICT
页码：
424-432
会议名称：
6th IFIP International Conference on Internet of Things, IFIP IoT 2023
会议时间：
2 November 2023 through 3 November 2023
摘要：
Smartphones have become essential components in the Internet of Medical Things (IoMT), providing convenient interfaces and advanced technology that enable interaction with various medical devices and sensors. This makes smartphones serve as gateways for sensitive data that could potentially affect patients’ health and privacy if compromised, making them primary targets for cybersecurity threats. Authentication is crucial for IoMT security, as its effectiveness relies on its resistance to any conditions of environment, device, or user. In this paper, we propose the Anomaly Location-based Authentication (ALBA) method using GPS technology and a lightweight unsupervised ML a...
