14 search results - page 1 / 3 » Injecting utility into anonymized datasets |
SIGMOD
2006
ACM
14 years 5 months ago
2006
ACM
Limiting disclosure in data publishing requires a careful balance between privacy and utility. Information about individuals must not be revealed, but a dataset should still be us...
KDD
2008
ACM
14 years 5 months ago
2008
ACM
Re-identification is a major privacy threat to public datasets containing individual records. Many privacy protection algorithms rely on generalization and suppression of "qu...
ICDE
2007
IEEE
14 years 6 months ago
2007
IEEE
k-Anonymity protects privacy by ensuring that data cannot be linked to a single individual. In a k-anonymous dataset, any identifying information occurs in at least k tuples. Much...
ICDE
2008
IEEE
15 years 5 months ago
2008
IEEE
Existing work on privacy-preserving data publishing cannot satisfactorily prevent an adversary with background knowledge from learning important sensitive information. The main cha...
ICDE
2008
IEEE
14 years 6 months ago
2008
IEEE
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-...