Key-based Reversible Data Masking for Business Intelligence Healthcare Analytics Platforms

Abstract

Business Intelligence (BI) is quickly becoming a very important tool for all aspects of data analytics. An area that lacks a strong implementation for BI is the healthcare field. BI healthcare analytics platforms facilitate the clinical analysis, financial analysis, supply chain analysis, as well as, fraud and HR analysis. The reason behind the lack of adoption in healthcare arises from the need to meet the legislated and perceived requirements of security and privacy when dealing with clinical information. A strong data masking module is developed based on the key-based reversible approach to protect patients' data privacy, while maintaining the data utility to meet the need for data analytics within BI platforms of the healthcare environment. To ensure the performance of the proposed module, a TPC-H Benchmark analysis is performed which verifies that the analytics results of the masked data are appropriate when compared to the existing masking and encryption methods. The developed module is shown to be secure against the common security threats such as linkage attacks and replay attacks. It uses minimal computational overhead when compared to its counterpart methods and meets the legal requirements to be used safely in the healthcare industry.