Trusted Composition of Internet of Medical Things over Imperfect Networks

Ehsan Ahmad (), Brian Larson and Abdulbasid Banga
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Ehsan Ahmad: College of Computing and Informatics, Saudi Electronic University, Riyadh 13323, Saudi Arabia
Brian Larson: Multitude Corporation, St. Paul, MN 55126, USA
Abdulbasid Banga: College of Computing and Informatics, Saudi Electronic University, Riyadh 13323, Saudi Arabia

Future Internet, 2024, vol. 16, issue 7, 1-18

Abstract: The Internet of Medical Things (IoMT) represents a specialized domain within the Internet of Things, focusing on medical devices that require regulatory approval to ensure patient safety. Trusted composition of IoMT systems aims to ensure high assurance of the entire composed system, despite potential variability in the assurance levels of individual components. Achieving this trustworthiness in IoMT systems, especially when using less-assured, commercial, off-the-shelf networks like Ethernet and WiFi, presents a significant challenge. To address this challenge, this paper advocates a systematic approach that leverages the Architecture Analysis & Design Language (AADL) along with Behavior Language for Embedded Systems with Software (BLESS) specification and implementation. This approach aims to provide high assurance on critical components through formal verification, while using less-assured components in a manner that maintains overall system determinism and reliability. A clinical case study involving an automated opioid infusion monitoring IoMT system is presented to illustrate the application of the proposed approach. Through this case study, the effectiveness of the systemic approach in achieving trusted composition of heterogeneous medical devices over less-assured networks is demonstrated.

Keywords: Architecture Analysis & Design Language; AADL; Behavior Language for Embedded Systems with Software; BLESS; IoT; IoMT; medical device interoperability; composition of medical devices; healthcare (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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