Privacy Preserving Data Publishing Anonymization Methods for Limiting Malicious Attacks in Healthcare Records

Abstract

In recent times, especially since the beginning of the new millennium, governments, industry players, IT firms and business enterprises have given more consideration to the use of data for their decision and operational processes. This data, that usually contain users, clients and customers’ information, is collected using varying infrastructure, instruments and techniques. The technological breakthroughs in the health industry and the digitalization of medical records i.e., transformation into Electronic Health Records (EHRs) brings about the possibilities of accessing health records in real-time anywhere through the use of big data, aimed at reducing cost and increasing profits within the healthcare industry. However with this advancement, threats to the privacy and security of healthcare records have inevitably creeped in because of malicious attacks. This paper is directed at addressing privacy and security related issues associated with big data i.e., Privacy Preserving Data Publishing (PPDP) methods useful for the medical world. It seeks to explore various possible methods and techniques that can render data anonymously by using anonymization processes i.e., untraceable to the original data owners. This restricts the possibilities of patient privacy infraction by malicious elements, while making the data available for analytical purposes. The anonymization process here is achieved through data publishers who stand as a middleman between data owners and the data recipient and ensures that the privacy of data owners is preserved at all times.