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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 ...
M. Ercan Nergiz, Chris Clifton
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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 ...
M. Ercan Nergiz, Chris Clifton
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($k$,$��$)-Anonymity: $k$-Anonymity with $��$-Differential Privacy
2017The explosion in volume and variety of data offers enormous potential for research and commercial use. Increased availability of personal data is of particular interest in enabling highly customised services tuned to individual needs. Preserving the privacy of individuals against reidentification attacks in this fast-moving ecosystem poses significant ...
Holohan, Naoise +3 more
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Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, 2006
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification. Recent studies show that a more sophisticated model is necessary to protect the association of individuals to sensitive information.
Raymond Chi-Wing Wong +3 more
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Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification. Recent studies show that a more sophisticated model is necessary to protect the association of individuals to sensitive information.
Raymond Chi-Wing Wong +3 more
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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 +2 more
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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 +2 more
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On Distributed k-Anonymization
Fundamenta Informaticae, 2009When 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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Differentially Private K-Anonymity
2014 12th International Conference on Frontiers of Information Technology, 2014Research 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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k-anonymous message transmission
Proceedings of the 10th ACM conference on Computer and communications security, 2003Informally, a communication protocol is sender k - anonymous if it can guarantee that an adversary, trying to determine the sender of a particular message, can only narrow down its search to a set of k suspects. Receiver k-anonymity places a similar guarantee on the receiver: an adversary, at best, can only narrow down the possible receivers to a set ...
Luis von Ahn +2 more
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Towards optimal k-anonymization
Data & Knowledge Engineering, 2008When releasing microdata for research purposes, one needs to preserve the privacy of respondents while maximizing data utility. An approach that has been studied extensively in recent years is to use anonymization techniques such as generalization and suppression to ensure that the released data table satisfies the k-anonymity property.
Tiancheng Li, Ninghui Li
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Mondrian Multidimensional K-Anonymity
22nd International Conference on Data Engineering (ICDE'06), 2006K-Anonymity has been proposed as a mechanism for protecting privacy in microdata publishing, and numerous recoding "models" have been considered for achieving 𝑘anonymity. This paper proposes a new multidimensional model, which provides an additional degree of flexibility not seen in previous (single-dimensional) approaches. Often this flexibility leads
K. LeFevre, D.J. DeWitt, R. Ramakrishnan
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Secure Distributed k-Anonymous Pattern Mining
Sixth International Conference on Data Mining (ICDM'06), 2006Privacy-Preserving Data Mining is an important area that studies privacy issues of data mining. When the goal is to share data mining results, two privacy-related problems may arise. The first one is how to compute the data-mining results among several parties without sharing the data. Cryptography-based primitives are the basic tool used to develop ad-
JIANG W, ATZORI, MAURIZIO
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