Abstract
With the challenge of contemporary mobile computing, quantified self-data need a well-established data service model based on information sources which takes individual privacy into account. This paper presents a lifelog attribute data portfolio (LLADP) that will be used for practically modeling life events and for digitizing such information. In this article, we also propose the privacy implications of lifelogging for each attribute. We designed an attribute portfolio on the basis of the kinds of lifelog services that are already provided in contemporary wearable devices. We aim to map real life models with computerized data models. However, life events may be impossible to completely record because of current device limitations. Thus, we aim to propose a lifelog attribute data portfolio (LLADP) using hybrid cloud management that takes privacy implications and a basic privacy policy into account.
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This work was supported by the Japan Society for the Promotion of Science (JSPS, KAKENHI Grant Number 15H02783).
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Chertchom, P. et al. (2018). A Lifelog Data Portfolio for Privacy Protection Based on Dynamic Data Attributes in a Lifelog Service. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. SNPD 2017. Studies in Computational Intelligence, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-319-62048-0_8
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