Research Article
A Secure Real Time Data Processing Framework for Personally Controlled Electronic Health Record (PCEHR) System
@INPROCEEDINGS{10.1007/978-3-319-23802-9_13, author={Khandakar Rabbi and Mohammed Kaosar and Md Rafiqul Islam and Quazi Mamun}, title={A Secure Real Time Data Processing Framework for Personally Controlled Electronic Health Record (PCEHR) System}, proceedings={International Conference on Security and Privacy in Communication Networks. 10th International ICST Conference, SecureComm 2014, Beijing, China, September 24-26, 2014, Revised Selected Papers, Part II}, proceedings_a={SECURECOMM}, year={2015}, month={12}, keywords={PCEHR Big data Apache kafka Apache storm Big data security}, doi={10.1007/978-3-319-23802-9_13} }- Khandakar Rabbi
Mohammed Kaosar
Md Rafiqul Islam
Quazi Mamun
Year: 2015
A Secure Real Time Data Processing Framework for Personally Controlled Electronic Health Record (PCEHR) System
SECURECOMM
Springer
DOI: 10.1007/978-3-319-23802-9_13
Abstract
An era of open information in the healthcare is now underway. This information can be considered as ‘Big data’, not only for its sheer volume but also for its complexity, diversity, and timeliness of data for any large eHealth System such as Personally Controlled Electronic Health Record (PCEHR). The system enables different person or organization to access, share, and manage their health data. Other challenges incorporated with the PCEHR data can be very excessive to capture, store, process and retrieve the insight knowledge in real time. Various PCEHR frameworks have been proposed in recent literature. However, big data challenges have not been considered in these frameworks. In this paper, we argue the PCEHR data should be considered as big data and the challenges of big data should be addressed when to design the framework of the PCEHR system. In doing so, we propose a PCEHR framework, which deals with real time big data challenges using the state-of-the-art technologies such as Apache Kafka and Apache Storm. At the same time the proposed framework ensures secure data communication using cryptographic techniques. Using a qualitative analysis, we show that the proposed framework addresses the big data challenges.
