A Game Theory Approach to Preserve Privacy in Hospital Management System

Abstract

Privacy preservation has become a major issue in data analysis applications. Hospital data is considered as an example to provide privacy preservation. When a data set is released to other parties for data analysis, privacy-preserving techniques are often required to reduce the possibility of identifying sensitive information about individuals. Protection of individual's privacy is a significant activity in data publishing. Sensitive information of each individual, whose data is published must be protected. Privacy issues are increasing in the process of collecting and publishing individual's personal data. Game theory approach plays an important role in price exchange-off to provide data sets based on the users, whose price is best and best action is taken. Here the data provider will be able to send securely (secure channel assumed) his private data, namely the data containing information that he does not want anyone else to knoworun-authorized modification, while transferring data from provider to collector or to other modules. To provide data privacy, protection will be the major challenge where multiple users are involved. In the proposed system Nash equilibrium approach of game theory is used to provide the data privacy protection while transferring data to other modules by calculating best payoff. The main focus of privacy preserving in data publishing is to enhance data modification by masking identity of individual and preserve sensitive information. Privacy preserving data publishing focuses on techniques for publishing data. Anonymization of the data is done by hiding the identity of individuals. Anonymization techniques, like generalization, multi-based generalization, suppression is designed for preserving privacy in data publishing. To protect data provider's privacy of individual's, the data collector performs anonymization techniques on data. Information suppliers would give more information if anonymity is powerfully assured. Data provider finds a suitable data collector who preserves user identity and data privacy. Data collector modifies the data such that modified data can guarantee privacy when released to other parties. Data user received data contains no privacy information of individuals from collector. This data can be used to perform analysis by the user. Quality of data received by data collector against the data sent by data provider and similarly quality of data received by data user against the data sent by data collector are analyzed and representing using graphs.