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» L-Cover: Preserving Diversity by Anonymity
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SDMW
2009
Springer
13 years 11 months ago
L-Cover: Preserving Diversity by Anonymity
To release micro-data tables containing sensitive data, generalization algorithms are usually required for satisfying given privacy properties, such as k-anonymity and l-diversity....
Lei Zhang 0004, Lingyu Wang, Sushil Jajodia, Alexa...
TDSC
2011
12 years 11 months ago
CASTLE: Continuously Anonymizing Data Streams
— Most of existing privacy preserving techniques, such as k-anonymity methods, are designed for static data sets. As such, they cannot be applied to streaming data which are cont...
Jianneng Cao, Barbara Carminati, Elena Ferrari, Ki...
ICDE
2009
IEEE
176views Database» more  ICDE 2009»
14 years 6 months ago
Efficient Table Anonymization for Aggregate Query Answering
Abstract-- Privacy protection is a major concern when microdata needs to be released for ad hoc analyses. This has led to a lot of recent research in privacy goals and table anonym...
Cecilia M. Procopiuc, Divesh Srivastava
VLDB
2007
ACM
137views Database» more  VLDB 2007»
14 years 5 months ago
Fast Data Anonymization with Low Information Loss
Recent research studied the problem of publishing microdata without revealing sensitive information, leading to the privacy preserving paradigms of k-anonymity and -diversity. k-a...
Gabriel Ghinita, Panagiotis Karras, Panos Kalnis, ...
SIGMOD
2010
ACM
274views Database» more  SIGMOD 2010»
13 years 9 months ago
K-isomorphism: privacy preserving network publication against structural attacks
Serious concerns on privacy protection in social networks have been raised in recent years; however, research in this area is still in its infancy. The problem is challenging due ...
James Cheng, Ada Wai-Chee Fu, Jia Liu