In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Prior work in differential privacy has produced techniques for answering aggregate queries over sensitive data in a privacypreserving way. These techniques achieve privacy by addi...
Xiaokui Xiao, Gabriel Bender, Michael Hay, Johanne...
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...
Secure coprocessors have traditionally been used as a keystone of a security subsystem, eliminating the need to protect the rest of the subsystem with physical security measures. ...
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...