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Interactive anonymization of sensitive data
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data, 2009There has been much recent work on algorithms for limiting disclosure in data publishing, however they have not been put to use in any toolkit for practicioners. We will demonstrate CAT, the Cornell Anonymization Toolkit, designed for interactive anonymization. CAT has an interface that is easy to use; it guides users through the process of preparing a
Xiaokui Xiao +2 more
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Data anonymization: k-anonymity and de-anonymization attacks
2017Η ανάγκη για πρόσβαση σε δεδομένα που αφορούν πολίτες ολοένα αυξάνεται τα τελευταία χρόνια. Αυτά τα δεδομένα μπορεί να έχουν συλλεχθεί από κυβερνήσεις ή επιχειρήσεις για διάφορους σκοπούς και λόγους. Παρόλα αυτά η δημοσίευση των δεδομένων μπορεί να προκαλέσει διάφορα θέματα εάν δεν ληφθούν κατάλληλα μέτρα.
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Anonymity-preserving data collection
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, 2005Protection of privacy has become an important problem in data mining. In particular, individuals have become increasingly unwilling to share their data, frequently resulting in individuals either refusing to share their data or providing incorrect data.
Zhiqiang Yang +2 more
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Dissemination of anonymized streaming data
Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems, 2015With the vision of the emergence of streaming data marketplaces, we study the problem of how to use a scalable dissemination infrastructure, composed by a number of brokers, to disseminate anonymized streaming data to a large number of clients. To satisfy the clients, who are trusted at different anonymity levels and have their own urgencies in ...
Yongluan Zhou +3 more
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Spectral anonymization of data.
2007Data anonymization is the process of conditioning a dataset such that no sensitive information can be learned about any specific individual, but valid scientific analysis can nevertheless be performed on it. It is not sufficient to simply remove identifying information because the remaining data may be enough to infer the individual source of the ...
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Data anonymization evaluation for big data and IoT environment
Information Sciences, 2022Geyong Min
exaly
An effective framework for data anonymity
2006Sharing microdata tables is a primary concern in today information society. Privacy issues can be an obstacle to the free flow of such information. In recent years, disclosure control techniques have been developed to modify microdata tables in order to be anonymous.
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Implications of Data Anonymization on the Statistical Evidence of Disparity
Management Science, 2022Heng Xu, Nan Zhang
exaly
Methods and tools for healthcare data anonymization: a literature review
International Journal of General Systems, 2023Gunnar Piho, Peeter Ross, Olga Vovk
exaly