Ruotsalainen, P. and Blobel, Bernd
(2018)
A Model for Calculated Privacy and Trust.
In: Blobel, Bernd and Yang, Bian, (eds.)
pHealth Ecosystems. Proc. of the 15th Int. Conf. on Wearable Micro and Nano Technologies for Personalized Health, 12-14 June 2018, Gjøvik, Norway.
Studies in Health Technology and Informatics, 249.
IOS Press, Amsterdam, pp. 29-37.
ISBN 978-1-61499-867-9.
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Abstract
A pHealth ecosystem is a community of service users and providers. It is also a dynamic socio-technical system. One of its main goals is to help users to maintain their personal health status. Another goal is to give economic benefit to stakeholders which use personal health information existing in the ecosystem. In pHealth ecosystems, a huge amount of health related data is collected and used by ...
Abstract
A pHealth ecosystem is a community of service users and providers. It is also a dynamic socio-technical system. One of its main goals is to help users to maintain their personal health status. Another goal is to give economic benefit to stakeholders which use personal health information existing in the ecosystem. In pHealth ecosystems, a huge amount of health related data is collected and used by service providers such as data extracted from the regulated health record and information related to personal characteristics, genetics, lifestyle and environment. In pHealth ecosystems, there are different kinds of service providers such as regulated health care service providers, unregulated health service providers, ICT service providers, researchers and industrial organizations. This fact together with the multidimensional personal health data used raises serious privacy concerns. Privacy is a necessary enabler for successful pHealth, but it is also an elastic concept without any universally agreed definition. Regardless of what kind of privacy model is used in dynamic socio-technical systems, it is difficult for a service user to know the privacy level of services in real life situations. As privacy and trust are interrelated concepts, the authors have developed a hybrid solution where knowledge got from regulatory privacy requirements and publicly available privacy related documents is used for calculation of service providers' specific initial privacy value. This value is then used as an estimate for the initial trust score. In this solution, total trust score is a combination of recommended trust, proposed trust and initial trust. Initial privacy level is a weighted arithmetic mean of knowledge and user selected weights. The total trust score for any service provider in the ecosystem can be calculated deploying either a beta trust model or the Fuzzy trust calculation method. The prosed solution is easy to use and to understand, and it can be also automated. It is possible to develop a computer application that calculates a situation-specific trust score, and to make it freely available on the Internet.
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