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A Novel Framework for Privacy-Preserving Data Publishing with Multiple Sensitive Attributes

Authors

Saud Al-Otaibi and lujain Al-Qurashi, Umm Al-Qura University, Saudi Arabia

Abstract

The world is now experiencing a great technological revolution, as many fields have become dependent on it. The use of technology by members of society has become daily. Data is collected on individuals by using smart technology applications in hospitals or companies. These organizations are managed through databases that record data about their customers. The collected data may include sensitive data (e.g., personal data) that individuals do not want to disclose. In order to continue development , we sometimes need to publish this data for the purposes of research, statistical studies or decision-making. The publication of this data constitutes a threat to the privacy of the customer as it can be exploited by the intruder. This research focuses on trying to provide Privacy-Preserving Data Publishing algorithm that preserves customer privacy with the possibility of publishing this data with less information loss.

Keywords

trust Privacy-Preserving Data Publishing (PPDP), l-diversity