Personal privacy preserving data publication: ?- Differential privacy perspective

Abstract

Personal privacy preservation has been very important topic in Internet of Things (IoT) and big data world from the recent years. Though, many research studiescontain lot of restrictions about the opponent awareness that protect personal privacy of individual’s information. When the opponenthas a prior idea about the sensitive attributes then only it is possible to restrict attacks on the personal data. Today Differential Privacy (DP) is a fresh shift in personal privacy preservation with conventional assumptions about the opponent knowledge. Differential privacy is a good proposal in gaining the interest in many fields of information technology which gives more insights to work on the modern differential privacy analysis motivates to implement algorithms from that one can get optimal solutions to the personal privacy problems. This menu script proposes an algorithm based on the idea of differential privacy along with the Game theory mechanism to address the data publication of continuous data generation of medical records.

KEYWORDS: PERSONAL PRIVACY, EQUIVALENCE CLASS, GENERALIZATION