Results 201 to 210 of about 47,561 (256)

Thoughts on k-Anonymization

22nd International Conference on Data Engineering Workshops (ICDEW'06), 2006
k-Anonymity is a method for providing privacy protection by ensuring that data cannot be traced to an individual. In a k-anonymous dataset, any identifying information occurs in at least k tuples. To achieve optimal and practical k-anonymity, recently, many different kinds of algorithms with various assumptions and restrictions have been proposed with ...
Mehmet Ercan Nergiz, Chris Clifton
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k-Anonymization Revisited

2008 IEEE 24th International Conference on Data Engineering, 2008
In this paper we introduce new notions of k-type anonymizations. Those notions achieve similar privacy goals as those aimed by Sweenie and Samarati when proposing the concept of k-anonymization: an adversary who knows the public data of an individual cannot link that individual to less than k records in the anonymized table. Every anonymized table that
Aristides Gionis, Arnon Mazza, Tamir Tassa   +2 more
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k-Anonymous data collection

Information Sciences, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sheng Zhong 0002, Zhiqiang Yang, Tingting Chen 0001   +2 more
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MULTIPLE RELEASES OF k-ANONYMOUS DATA SETS AND k-ANONYMOUS RELATIONAL DATABASES

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2012
In data privacy, the evaluation of the disclosure risk has to take into account the fact that several releases of the same or similar information about a population are common. In this paper we discuss this issue within the scope of k-anonymity. We also show how this issue is related to the publication of privacy protected databases that consist of ...
Klara Stokes, Vicenç Torra
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On Distributed k-Anonymization

Fundamenta Informaticae, 2009
When a database owner needs to disclose her data, she can k-anonymize her data to protect the involved individuals' privacy. However, if the data is distributed between two owners, then it is an open question whether the two owners can jointly k-anonymize the union of their data, such that the information suppressed in one owner's data is not revealed ...
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K-Anonymity for Crowdsourcing Database

IEEE Transactions on Knowledge and Data Engineering, 2014
In crowdsourcing database, human operators are embedded into the database engine and collaborate with other conventional database operators to process the queries. Each human operator publishes small HITs (Human Intelligent Task) to the crowdsourcing platform, which consist of a set of database records and corresponding questions for human workers. The
Sai Wu, Xiaoli Wang 0002, Sheng Wang 0011, Zhenjie Zhang, Anthony K. H. Tung   +4 more
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Differentially Private K-Anonymity

2014 12th International Conference on Frontiers of Information Technology, 2014
Research in privacy preserving data publication can be broadly categorized in two classes. Syntactic privacy definitions have been under the cursor of the research community for the past many years. A lot of research is primarily dedicated to developing algorithms and notions for syntactic privacy that thwart the re-identification attacks.
Adeel Anjum, Adnan Anjum
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Hardness of \(k\)-anonymous microaggregation

Discret. Appl. Math., 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Florian Thaeter, Rüdiger Reischuk
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