Secured e-health data retrieval in DaaS and Big Data

Big Data is one of rising IT trends such as cloud computing, social networking or ubiquitous computing. Big Data can offer beneficial scenarios in the e-health arena. However, one of the scenarios can be that Big Data needs to be kept secured for a long time in order to gain its benefits such as finding cures for infectious diseases and keeping patients´ privacy. From this connection, it is beneficial to analyze Big Data to make meaningful information while the data are stored in a secure manner. Thus, the analysis of various database encryption techniques is essential. In this study, we simulated 3 types of technical environments such as Plain-text, Microsoft Built-in Encryption, and custom Advanced Encryption Standard using Bucket Index in Data-as-a-Service. The results showed that custom AES-DaaS has faster range query response time than MS built-in encryption. In addition, while carrying out the scalability test, we acknowledged there are performance thresholds according to physical IT resources. Therefore, for the purpose of efficient Big Data management in e-health, it is noteworthy to examine its scalability limits as well even if it is under cloud computing environment. Furthermore, when designing an e-health database, both patients´ privacy and system performance needs to be dealt as top priorities.