Privacy Preserving Issues in Data Publishing

Abstract: 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 use their data for predictive analytics. The organizations should not reveal the sensitive details of the record owners for any cause. In general the data privacy is preserved with data anonymization. There are algorithms such as k-anonymity, l-diversity and t-closeness for data anonymization. On anonymizing the data, there are threats that can disclose the information about the record owner. In this paper we discussed about the threats that affects the privacy of record owners in data publishing.

Keywords: privacy, data publishing, privacy threats, anonymization, privacy protection.