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ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
10 years 11 months ago
Fine-Grain Perturbation for Privacy Preserving Data Publishing
— Recent work [12] shows that conventional privacy preserving publishing techniques based on anonymity-groups are susceptible to corruption attacks. In a corruption attack, if th...
Rhonda Chaytor, Ke Wang, Patricia Brantingham
SDM
2009
SIAM
331views Data Mining» more  SDM 2009»
11 years 1 months ago
Privacy Preservation in Social Networks with Sensitive Edge Weights.
With the development of emerging social networks, such as Facebook and MySpace, security and privacy threats arising from social network analysis bring a risk of disclosure of con...
Jie Wang, Jinze Liu, Jun Zhang, Lian Liu
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
11 years 4 months ago
Privacy-Preserving Data Mining through Knowledge Model Sharing
Privacy-preserving data mining (PPDM) is an important topic to both industry and academia. In general there are two approaches to tackling PPDM, one is statistics-based and the oth...
Patrick Sharkey, Hongwei Tian, Weining Zhang, Shou...
ICDE
2005
IEEE
118views Database» more  ICDE 2005»
11 years 5 months ago
A Framework for High-Accuracy Privacy-Preserving Mining
To preserve client privacy in the data mining process, a variety of techniques based on random perturbation of individual data records have been proposed recently. In this paper, ...
Shipra Agrawal, Jayant R. Haritsa
SDM
2007
SIAM
130views Data Mining» more  SDM 2007»
10 years 5 months ago
Towards Attack-Resilient Geometric Data Perturbation
Data perturbation is a popular technique for privacypreserving data mining. The major challenge of data perturbation is balancing privacy protection and data quality, which are no...
Keke Chen, Gordon Sun, Ling Liu
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