Record linkage is a technique for integrating data from sources or providers where direct access to the data is not possible due to security and privacy considerations. This is a very common scenario for medical data, as patient privacy is a significant concern. To avoid privacy leakage, researchers have adopted k-anonymity to protect raw data from re-identification however they cannot avoid as...

Microaggregation is one of the most commonly employed microdata protection methods. The basic idea of microaggregation is to anonymize data by aggregating original records into small groups of at least k elements and, therefore, preserving k-anonymity. Usually, in order to avoid information loss, when records are large, i.e., the number of attributes of the data set is large, this data set is s...

K-anonymity is an effective model for protecting privacy while publishing data, which can be implemented by different ways. Among them, local generalization are popular because of its low information loss. But such algorithms are generally computation expensive making it difficult to perform well in the case of large amount of data. In order to solve this problem, this paper proposes a clusteri...

Cloud computing is attracting more and more researchers and enterprises, because it can deal with massive data with cheap commodity computers. Medical data are very important for disease analysis in order to better serve the patients, but the privacy of patients must be handled first. In this paper, we apply the cloud platform to build a medical data center for data mining, and propose an impro...

There are different methods to build an anonymity service using MIXes. A substantial decision for doing so is the method of choosing the MIX route. In this paper we compare two special configurations: a fixed MIX route used by all participants and a network of freely usable MIXes where each participant chooses his own route. The advantages and disadvantages in respect to the freedom of choice a...