Abstract
In recent years the amount of digital data in the world has risen immensely. But, the more information exists, the greater is the possibility of its unwanted disclosure. Thus, the data privacy protection has become a pressing problem of the present time.
The task of individual privacy-preserving is being thoroughly studied nowadays. At the same time, the problem of statistical disclosure control for collective (or group) data is still open.
In this paper we propose an effective and relatively simple (wavelet-based) way to provide group anonymity in collective data. We also provide a real-life example to illustrate the method.
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Chertov, O., Tavrov, D. (2010). Group Anonymity. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications. IPMU 2010. Communications in Computer and Information Science, vol 81. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14058-7_61
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DOI: https://doi.org/10.1007/978-3-642-14058-7_61
Publisher Name: Springer, Berlin, Heidelberg
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