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222 CHAPTER 8 BLOCKCHAIN IN HEALTHCARE: CHALLENGES AND SOLUTIONS

8.6 CONCLUSION AND DISCUSSION
In this chapter, two pressing challenges of healthcare big data were discussed. Firstly, it discusses the
existing privacy regulations and secondly, it discusses how blockchain addresses those privacy regu-
lations with different available solutions. This chapter provides a detailed elaboration on blockchain
opportunities, challenges, and healthcare solutions. While discussing the available regulations, we
identified the major design principles and prerequisites needed for blockchain system development.
From our study, we noticed that regulations such as GDPR and HIPAA do not support on-chain per-
sonal data storing. However, off-chain blockchain, encrypted private storing is a popular alternative
blockchain architecture to address the existing issues. Overall, the blockchain has a varied range of
potentials in medical data that invites numerous research opportunities in this sector. Overall this chap-
ter highlights the impact of blockchain on the privacy of healthcare big data as well as proposes a so-
lution to decrease the impact on the long-term. The technical, strategical, economical, and regulatory
aspects of blockchain and healthcare big data privacy is understandable as well as implementable with
the help of this chapter. Our future goal is to develop a fully fledged healthcare data sharing and identity
sharing platform.

REFERENCES
[1] D. Munro, Data Breaches in Healthcare Totaled Over 112 Million Records in 2015, vol. 31, Forbes, New
York, NY, 2015.
[2] S. Banerjee, T. Hemphill, P. Longstreet, Wearable devices and healthcare: data sharing and privacy, Inf. Soc.
34 (1) (2018) 49–57.
[3] A.E. Hassanien, N. Dey, S. Borra (Eds.), Medical Big Data and Internet of Medical Things: Advances, Chal-
lenges and Applications, Taylor & Francis, 2019.
[4] M. Ahmed, A.S.B. Ullah, Infrequent pattern mining in smart healthcare environment using data summari-
zation. J. Supercomput. 74 (2018) 5041, https://doi.org/10.1007/s11227-018-2376-8.
[5] N. Dey, A.E. Hassanien, C. Bhatt, A.S. Ashour, S.C. Satapathy (Eds.), Internet of Things and Big Data An-
alytics Toward Next-Generation Intelligence, Springer International Publishing, 2018.
[6] M.S. Kamal, S. Parvin, A.S. Ashour, F. Shi, N. Dey, De-Bruijn graph with MapReduce framework towards
metagenomic data classification, Int. J. Inf. Technol. 9 (1) (2017) 59–75.
[7] B.S.P. Mishra, H. Das, S. Dehuri, A.K. Jagadev (Eds.), Cloud Computing for Optimization: Foundations,
Applications, and Challenges, In: vol. 39, Springer International Publishing, 2018.
[8] C. Holotescu, Understanding blockchain opportunities and challenges, in: The International Scientific Con-
ference eLearning and Software for Education, vol. 4, Carol I National Defence University, 2018,
pp. 275–283.
[9] M.A. Sahi, H. Abbas, K. Saleem, X. Yang, A. Derhab, M.A. Orgun, … A. Yaseen, Privacy preservation in
e-healthcare environments: state of the art and future directions, IEEE Access 6 (2018) 464–478.
[10] P.K. Pattnaik, S.S. Rautaray, H. Das, J. Nayak (Eds.), Progress in computing, analytics and networking,
Proceedings of ICCAN 2017, In: vol. 710, Springer, 2018.
[11] J.D. Halamka, A. Lippman, A. Ekblaw, The potential for blockchain to transform electronic health records,
Harv. Bus. Rev. 3 (2017). Retrieved from: https://hbr.org/2017/03/the-potential-for-blockchain-to-
transform-electronic-health-records.
[12] X. Yue, H. Wang, D. Jin, M. Li, Healthcare data gateways: found healthcare intelligence on blockchain with
novel privacy risk control, J. Med. Syst. 40 (10) (2016) 218.