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Mobile and wearable systems have generated unprecedented interest in recent years, particularly in the domain of mobile health (mHealth) where carried or worn devices are used to collect health-related information about the observed person. Much of the information – whether physiological, behavioral, or social – collected by mHealth systems is sensitive and highly personal; it follows that mHealth systems should, at the very least, be deployed with mechanisms suitable for ensuring confidentiality of the data it collects. Additional properties – such as integrity of the data, source authentication of data, and data freshness – are also desirable to address other security, privacy, and safety issues.
Developing systems that are robust against capable adversaries (including physical attacks) is, and has been, an active area of research. While techniques for protecting systems that handle sensitive data are well-known today, many of the solutions in use today are not well suited for mobile and wearable systems, which are typically limited with respect to power, memory, computation, and other capabilities.
In this paper we look at prior research on developing trustworthy mobile and wearable systems. To survey this topic we begin by discussing solutions for securing computing systems that are not subject to the type of strict constraints associated with mobile and wearable systems. Next, we present other efforts to design and implement trustworthy mobile and wearable systems. We end with a discussion of future directions.
Bibliographic citation for this report: [plain text] [BIB] [BibTeX] [Refer]
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Travis W. Peters, "A Survey of Trustworthy Computing on Mobile & Wearable Systems." Dartmouth Computer Science Technical Report TR2017-823, May 2017.
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