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Enhancing Privacy for Big Data in Healthcare Domain based on Cryptographic and Decentralized Technology Methods
Tahir Yinka Olaosebikan1, Su-Cheng Haw2, Gaik-Yee Chan3

1Tahir Yinka Olaosebikan, Department of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia.
2Su-Cheng Haw, Department of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia.
3Gaik-Yee Chan, Department of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia.
Manuscript received on 26 September 2019 | Revised Manuscript received on 05 October 2019 | Manuscript Published on 22 October 2019 | PP: 129-135 | Volume-8 Issue-3S October 2019 | Retrieval Number: C10231083S19/2019©BEIESP | DOI: 10.35940/ijrte.C1023.1083S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Privacy is one of the biggest concerns that hinder most organizations to adopt the Big Data technology. Some mechanisms and systems have been set-up to handle huge databases. Nevertheless, the scalability requirements of Big Data are far beyond the conventional databases to handle. Therefore, it is trivial to set-up scalable privacy algorithms for conventional databases. Most data are stored in a single location, which means the records it keeps are open and effortlessly irrefutable to third parties. Centralized versions of this data make it too easy for hackers to attack. As such, in this paper, we present the opportunities and challenges of implementing cryptography and blockchain for privacy perseverance in Big Data, focusing in the healthcare domain. In addition, we also present some use cases of integrating Directed Acyclic Graph (DAG) into healthcare database framework for anchoring information security and privacy.
Keywords: Big Data, Cryptography, Symmetric Encryption, Directed Acyclic Graph, Blockchain, IOTA.
Scope of the Article: Big Data Analytics for Social Networking using IoT