Abstract. One of the emerging concepts in microdata protection is k-anonymity, introduced by Samarati and Sweeney. k-anonymity provides a simple and efficient approach to protect private individual information and is gaining increasing popularity. k-anonymity requires that every tu-ple(record) in the microdata table released be indistinguishably related to no fewer than k respondents. In this paper, we introduce two new vari-ants of the k-anonymity problem, namely, the Restricted k-anonymity problem and Restricted k-anonymity problem on attribute (where sup-pressing the entire attribute is allowed). We prove that both problems are NP-hard for k ≥ 3. The results imply the main results obtained by Meyerson and Williams. On the positive side, ...
Abstract: The concept of k-anonymity has been proposed as an effective way to anonymise microdata, w...
Data de-identification reconciles the demand for release of data for research purposes and the deman...
Recent research studied the problem of publishing microdata without revealing sensitive information,...
The problem of publishing personal data without giving up privacy is becoming increasingly important...
Abstract. Existing privacy regulations together with large amounts of available data have created a ...
K-Anonymity has been proposed as a mechanism for privacy protection in microdata publishing, and num...
We consider the problem of releasing a table containing personal records, while ensuring individual ...
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymi...
The NP-hard \textsck-Anonymity} problem asks, given an~n × m-matrix~M over a fixed alphabet and an i...
Micro-data protection is a hot topic in the eld of Statis-tical Disclosure Control (SDC), that has g...
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymi...
Microdata protection is a hot topic in the field of Statistical Disclosure Control, which has gained...
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymi...
We suggest a user-oriented approach to combinatorial data anonymization. A data matrix is called k-a...
Numerous privacy models based on the k-anonymity property and extending the k-anonymity model have b...
Abstract: The concept of k-anonymity has been proposed as an effective way to anonymise microdata, w...
Data de-identification reconciles the demand for release of data for research purposes and the deman...
Recent research studied the problem of publishing microdata without revealing sensitive information,...
The problem of publishing personal data without giving up privacy is becoming increasingly important...
Abstract. Existing privacy regulations together with large amounts of available data have created a ...
K-Anonymity has been proposed as a mechanism for privacy protection in microdata publishing, and num...
We consider the problem of releasing a table containing personal records, while ensuring individual ...
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymi...
The NP-hard \textsck-Anonymity} problem asks, given an~n × m-matrix~M over a fixed alphabet and an i...
Micro-data protection is a hot topic in the eld of Statis-tical Disclosure Control (SDC), that has g...
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymi...
Microdata protection is a hot topic in the field of Statistical Disclosure Control, which has gained...
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymi...
We suggest a user-oriented approach to combinatorial data anonymization. A data matrix is called k-a...
Numerous privacy models based on the k-anonymity property and extending the k-anonymity model have b...
Abstract: The concept of k-anonymity has been proposed as an effective way to anonymise microdata, w...
Data de-identification reconciles the demand for release of data for research purposes and the deman...
Recent research studied the problem of publishing microdata without revealing sensitive information,...