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@INPROCEEDINGS{,
     author = {Kilany, Rima and Maria, Sokhn and Hellani, Hussein and Shabani, Shaban},
      month = sep,
      title = {Towards Flexible K-Anonymity},
  booktitle = {7th International Conference on Knowledge Engineering and Semantic Web},
       year = {2016},
      pages = {288-297},
  publisher = {Springer},
   location = {Prague, Czech Republic},
       isbn = {978-3-319-45880-9},
        url = {http://link.springer.com/chapter/10.1007/978-3-319-45880-9_22},
        doi = {10.1007/978-3-319-45880-9_22},
   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.}
}