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A k-anonymity privacy-preserving approach in wireless medical monitoring environments

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Abstract

With the proliferation of wireless sensor networks and mobile technologies in general, it is possible to provide improved medical services and also to reduce costs as well as to manage the shortage of specialized personnel. Monitoring a person’s health condition using sensors provides a lot of benefits but also exposes personal sensitive information to a number of privacy threats. By recording user-related data, it is often feasible for a malicious or negligent data provider to expose these data to an unauthorized user. One solution is to protect the patient’s privacy by making difficult a linkage between specific measurements with a patient’s identity. In this paper we present a privacy-preserving architecture which builds upon the concept of k-anonymity; we present a clustering-based anonymity scheme for effective network management and data aggregation, which also protects user’s privacy by making an entity indistinguishable from other k similar entities. The presented algorithm is resource aware, as it minimizes energy consumption with respect to other more costly, cryptography-based approaches. The system is evaluated from an energy-consuming and network performance perspective, under different simulation scenarios.

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Acknowledgments

This research has been co-funded by the European Union (Social Fund) and Greek national resources under the framework of the “Archimedes III: Funding of Research Groups in TEI of Athens” project of the “Education & Lifelong Learning” Operational Programme.

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  1. Department of Informatics, Technological Educational Institution of Athens, Athens, Greece

    Petros Belsis & Grammati Pantziou

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  1. Petros Belsis
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  2. Grammati Pantziou
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Correspondence to Petros Belsis.

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Belsis, P., Pantziou, G. A k-anonymity privacy-preserving approach in wireless medical monitoring environments. Pers Ubiquit Comput 18, 61–74 (2014). https://doi.org/10.1007/s00779-012-0618-y

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