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Privacy preserving data mining has been investigated extensively. The previous works mainly fall into two categories, perturbation and randomization based approaches and secure multi-party computation based approaches. The earlier perturbation and randomization approaches have a step to reconstruct the original data distribution. The new research in this area adopts different data distortion methods...
Perturbation method is a very important technique in privacy preserving data mining. In this technique, loss of information versus preservation of privacy is always a trade off. The question is, how much are the users willing to compromise their privacy? This is a choice that changes from individual to individual. In this paper, we propose an individually adaptable perturbation model, which enables...
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