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» Probabilistic Inference Protection on Anonymized Data
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ICDM
2010
IEEE
150views Data Mining» more  ICDM 2010»
13 years 2 months ago
Probabilistic Inference Protection on Anonymized Data
Background knowledge is an important factor in privacy preserving data publishing. Probabilistic distributionbased background knowledge is a powerful kind of background knowledge w...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Ke Wang, Y...
ICDE
2009
IEEE
1081views Database» more  ICDE 2009»
15 years 4 months ago
Modeling and Integrating Background Knowledge in Data Anonymization
Recent work has shown the importance of considering the adversary’s background knowledge when reasoning about privacy in data publishing. However, it is very difficult for the d...
Tiancheng Li, Ninghui Li, Jian Zhang
FOSSACS
2008
Springer
13 years 6 months ago
Compositional Methods for Information-Hiding
Protocols for information-hiding often use randomized primitives to obfuscate the link between the observables and the information to be protected. The degree of protection provide...
Christelle Braun, Konstantinos Chatzikokolakis, Ca...
CCS
2010
ACM
13 years 5 months ago
In search of an anonymous and secure lookup: attacks on structured peer-to-peer anonymous communication systems
The ability to locate random relays is a key challenge for peer-to-peer (P2P) anonymous communication systems. Earlier attempts like Salsa and AP3 used distributed hash table look...
Qiyan Wang, Prateek Mittal, Nikita Borisov
ICDCS
2009
IEEE
14 years 2 months ago
CAP: A Context-Aware Privacy Protection System for Location-Based Services
We address issues related to privacy protection in location-based services (LBS). Most existing research in this field either requires a trusted third-party (anonymizer) or uses ...
Aniket Pingley, Wei Yu, Nan Zhang 0004, Xinwen Fu,...