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» Transforming data to satisfy privacy constraints
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ICDE
2007
IEEE
115views Database» more  ICDE 2007»
14 years 6 months ago
MultiRelational k-Anonymity
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...
Mehmet Ercan Nergiz, Chris Clifton, A. Erhan Nergi...
ICDM
2006
IEEE
131views Data Mining» more  ICDM 2006»
13 years 11 months ago
Transforming Semi-Honest Protocols to Ensure Accountability
The secure multi-party computation (SMC) model provides means for balancing the use and confidentiality of distributed data. This is especially important in the field of privacy...
Wei Jiang, Chris Clifton
CSFW
2009
IEEE
13 years 11 months ago
Achieving Security Despite Compromise Using Zero-knowledge
One of the important challenges when designing and analyzing cryptographic protocols is the enforcement of security properties in the presence of compromised participants. This pa...
Michael Backes, Martin P. Grochulla, Catalin Hritc...
EUC
2008
Springer
13 years 6 months ago
Privacy Engine for Context-Aware Enterprise Application Services
Satisfying the varied privacy preferences of individuals, while exposing context data to authorized applications and individuals, remains a major challenge for context-aware compu...
Marion Blount, John Davis, Maria Ebling, William F...
PODS
2004
ACM
120views Database» more  PODS 2004»
14 years 5 months ago
Locally Consistent Transformations and Query Answering in Data Exchange
Data exchange is the problem of taking data structured under a source schema and creating an instance of a target schema. Given a source instance, there may be many solutions ? ta...
Marcelo Arenas, Pablo Barceló, Ronald Fagin...