Privacy preserving data mining has been investigated extensively. The previous works mainly fall into two categories, perturbation and randomization based approaches and secure mu...
Li Liu, Murat Kantarcioglu, Bhavani M. Thuraisingh...
Reluctance of data owners to share their possibly confidential or proprietary data with others who own related databases is a serious impediment to conducting a mutually beneficia...
Ashish P. Sanil, Alan F. Karr, Xiaodong Lin, Jerom...
Randomization has been a primary tool to hide sensitive private information during privacy preserving data mining.The previous work based on spectral filtering, show the noise ma...
The recent investigation of privacy-preserving data mining and other kinds of privacy-preserving distributed computation has been motivated by the growing concern about the privacy...
Hiranmayee Subramaniam, Rebecca N. Wright, Zhiqian...
Randomization is an economical and efficient approach for privacy preserving data mining (PPDM). In order to guarantee the performance of data mining and the protection of individ...