Breaking Implicit Trust in Point-of-Care Medical Technology: A Cyber-Physical Attestation Approach
Abstract
Digital microfluidics biochips are an emerging technology that are increasingly being evaluated as a viable platform for rapid diagnosis and point-of-care field deployment. In such a technology, processing errors are inherent. Cyber-physical digital biochips offer higher reliability through the inclusion of automated error recovery mechanisms that can reconfigure the electrode array. The potential exists for attack on these systems by confusing the reconfiguration activity. Recent research has begun to explore security vulnerabilities of digital microfluidic systems. In this work we use the Multiple Security Domain Nondeducibility (MSDND) framework to explore vulnerabilities that exist due to implicit trust. Specifically we examine Stuxnet-type threats that result in the disruption of information flow paths, and how creating beneficial paths will prevent threats from "hiding" behind Nondeducibility.
Recommended Citation
F. Love and B. M. McMillin, "Breaking Implicit Trust in Point-of-Care Medical Technology: A Cyber-Physical Attestation Approach," Proceedings of the 41st IEEE Annual Computer Software and Applications Conference (2017, Turin, Italy), vol. 2, pp. 242 - 247, IEEE Computer Society, Jul 2017.
The definitive version is available at https://doi.org/10.1109/COMPSAC.2017.74
Meeting Name
41st IEEE Annual Computer Software and Applications Conference, COMPSAC 2017 (2017: Jul. 4-8, Turin, Italy)
Department(s)
Computer Science
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Biochips; Cyber-Physical Systems; Digital Microfluidics; Information Flow Security; Point-Of-Care Diagnostics
International Standard Book Number (ISBN)
978-1-5386-0367-3
International Standard Serial Number (ISSN)
0730-3157
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 IEEE Computer Society, All rights reserved.
Publication Date
01 Jul 2017