Abstract
Big data analytics in healthcare present a potentially powerful means for addressing public health emergencies such as the COVID-19 pandemic. A challenging issue for health data to be used, however, is the protection of privacy. Research on big data privacy, especially in relation to healthcare, is still at an early stage and there is a lack of guidelines or best practice strategies for big data privacy protection. Moreover, while academic discourse focuses on individual privacy, research evidence shows that there are cases such as mass surveillance through sensing and other IoT technologies where the privacy of groups needs also to be considered. This paper explores these challenges, focusing on health data analytics; we identify and analyse privacy threats and implications for individuals and groups and we evaluate recent privacy preserving techniques for contact tracing.
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Mavriki, P., Karyda, M. (2020). Big Data Analytics in Healthcare Applications: Privacy Implications for Individuals and Groups and Mitigation Strategies. In: Themistocleous, M., Papadaki, M., Kamal, M.M. (eds) Information Systems. EMCIS 2020. Lecture Notes in Business Information Processing, vol 402. Springer, Cham. https://doi.org/10.1007/978-3-030-63396-7_35
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