Abstract
Data published online nowadays needs a high level of privacy to gain confidentiality as well as to maintain the privacy laws. The focus on k-anonymity enhancements along the last decade, allows this method to be elected as the starting point of any research. In this paper we focus on the external anonymization through a new method: the « Flexible k-anonymity » . It aims to anonymize external published data, by defining a semantic ontology that distinguishes between sparse and abundant quasi-identifiers, and describes aggregation levels relations, in order to achieve adequate k-blocks. For the validation of our proposal, we apply the aforementioned anonymization method to the Comiqual dataset. Comiqual (Collaborative measurement of internet quality), is a large-scale measurement platform for assessing the internet quality access of mobile and ADSL users by collecting mobility traces and private data related to internet metric values.
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Kilany, R., Sokhn, M., Hellani, H., Shabani, S. (2016). Towards Flexible K-Anonymity. In: Ngonga Ngomo, AC., Křemen, P. (eds) Knowledge Engineering and Semantic Web. KESW 2016. Communications in Computer and Information Science, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-45880-9_22
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DOI: https://doi.org/10.1007/978-3-319-45880-9_22
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