Research Area: Internet of Things
This paper aims to advance the field of data anonymization within the context of Internet of Things (IoT), an environment where data collected may contain sensitive information about users. Specifically, we propose a privacy-preserving data publishing alternative that extends the privacy requirement to the data collection phase. Because our proposal offers privacy-preserving conditions in both the data collecting and publishing, it is suitable for scenarios where a central node collects personal data supplied by a set of devices, typically associated with individuals, without these having to assume trust in the collector. In particular, to limit the risk of individuals re-identification, the probabilistic k-anonymity property is satisfied during the data collection process and the k-anonymity property is satisfied by the data set derived from the anonymization process. To carry out the anonymous sending of personal data during the collection process, we introduce the delocalized-record chain, a new mechanism of anonymous communication aimed at multi-user environments to collaboratively protect information, which by not requiring third-party intermediaries makes it especially suitable for private IoT networks (besides public IoT networks).
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Author(s) Name: Mercedes Rodriguez-Garcia; María-ángeles Cifredo-Chacón; Ángel Quirós-Olozábal
Journal name: IEEE Access
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Publisher name: IEEE
DOI: 10.1109/ACCESS.2020.3028063
Volume Information: Volume: 8, Page(s): 180738 - 180749
