USER-CENTRIC PRIVACY PRESERVATION SOLUTION TO CONTROL THIRD PARTY ACCESS IN DIGITAL DATABASES

Abstract

The world is changing rapidly as technology advancements. Today, everything is e-enabled and human-linked information is digitally stored in digital databases, files and so on. Information privacy is a human right but, many privacy breaching incidents prove that, privacy has been threatened remarkably. Privacy is individualistic and dynamic in its nature. Many institutions, which collect human information, look at the privacy through the lens of a common pre-defined privacy policy or act. Such coarse-grain privacy preservation leads to violate individual’s specific privacy requirements. Simply, user-centric privacy preservation is not guaranteed. The author attempts to solve this human critical problem by proposing a fine-grain privacy preservation solution. A unique conceptual framework is presented with a novel notion of Key Privacy Determinant Attributes (KPDA) Index. User’s specific privacy perspectives will be captured through KPDA Index abstractly. However intelligent algorithms dynamically derive user sensitive database attributes to hide, when controlling third party access.