Releasing person-specific data could potentially reveal sensitive information about individuals. k-anonymization is a promising privacy protection mechanism in data publishing. Although substantial research has been conducted on k-anonymization and its extensions in recent years, only a few prior works have considered releasing data for some specific purpose of data analysis. This paper present...

Data publishing is recently focused more for the data analysis. In recent days, the data creation is enormous in all the fields. Predictive analytics uses all the data collected from various sources for predicting the future even though there is uncertainty in information gathered. The data used for analysis should not affect the privacy for the record owners. In all the sectors, organizations ...

This paper mainly deals with the issue of privacy preserving in data mining while collaborating n number of parties and trying to maintain confidentiality of all data providers details while collaborating their database. Here two type of attacks are addressed “insider attack” and “outsider attack”. In insider attack, the data providers use their own records and try to retrieve other data provid...

In the constantly developing world, e-health systems hold great promise for improving global access to healthcare services. Current significant technological visions of innovation in healthcare systems identify an approach to join different technological sectors and the need for technological platforms as well. These are: standardized electronic health records (eHR), aggregated public health da...

Data publishing generates much concern over the protection of individual privacy. Recent studies consider cases where the adversary may possess different kinds of knowledge about the data. In this paper, we show that knowledge of the mechanism or algorithm of anonymization for data publication can also lead to extra information that assists the adversary and jeopardizes individual privacy. In p...

In this paper, we reflect on the use of visualization techniques for analyzing electronic health record data with privacy concerns. Privacy-preserving data visualization is a relatively new area of research compared to the more established research areas of privacy-preserving data publishing and data mining. We describe the opportunities and challenges for privacy-preserving visualization of el...

The abundance and availability of personal information online and from ambient sensors has lead to an increasing rate in occurrences of privacy breaches and potential security harms to individuals. Yet, access to these information is critical for the success of many beneficial applications such as population health studies or urban planning. During this research paper we design an integrated se...

Privacy-preserving data publishing has been a heated research topic in the last decade. Numerous ingenious attacks on users’ privacy and defensive measures have been proposed for the sharing of various data, varying from relational data, social network data, spatiotemporal data, to images and videos. Speech data publishing, however, is still untouched in the literature. To fill this gap, we stu...