Abstract
We present a novel de-anonymization attack on mobility trace data and social data. First, we design an Unified Similarity (US) measurement, based on which we present a US based De-Anonymization (DA) framework which iteratively de-anonymizes data with an accuracy guarantee. Then, to de-anonymize data without the knowledge of the overlap size between the anonymized data and the auxiliary data, we generalize DA to an Adaptive De-Anonymization (ADA) framework. Finally, we examine DA/ADA on mobility traces and social data sets.
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Ji, S., Li, W., Srivatsa, M., He, J.S., Beyah, R. (2014). Structure Based Data De-Anonymization of Social Networks and Mobility Traces. In: Chow, S.S.M., Camenisch, J., Hui, L.C.K., Yiu, S.M. (eds) Information Security. ISC 2014. Lecture Notes in Computer Science, vol 8783. Springer, Cham. https://doi.org/10.1007/978-3-319-13257-0_14
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DOI: https://doi.org/10.1007/978-3-319-13257-0_14
Publisher Name: Springer, Cham
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