Big data facilitates the processing and management of huge amounts of data. In health, the main information source is the electronic health record with others being the Internet and social media. Health-related data refers to storage in big data based on and shared via electronic means. Why are criminal organisations interested in this data? These organisations can blackmail people with information related to their health condition or sell the information to marketing companies, etc. This article analyses healthcare-related big data security and proposes different solutions. There are different techniques available to help preserve privacy such as data modification techniques, cryptographic methods and protocols for data sharing, query auditing methods and others that are analysed in this research work. Although there remains much to do in the field of big data security, research in this area is moving forward, both from a scientific and commercial point of view.


[1] Aggarwal, Charu C., Yu, Philip S. (2008) Privacy-Preserving Data Mining: Models and Algorithms. Springer.

[2] Atallah MJ, Blanton M, Fazio N, Frikken KB. (2009). Dynamic and efficient key management for access hierarchies. ACM Transactions on Information and System Security, 12(3), 1–43.

[3] Backes M, Cachin C, Oprea M. (2006). Secure key-updating for lazy revocation. In Proceedings of 11th European Symposium on Research in Computer Security, 327– 346.

[4] Brinkmann B, Bowera M, Stengel K, Worrell G, Steada M. (2009). Large-scale electrophysiology: Acquisition, compression, encryption, and storage of big data, Journal of Neuroscience Methods, 180, 185–192.

[5] Cho D, Kim S, Yeo S. (2016). Double Privacy Layer Architecture for Big Data Framework. International Journal of Software Engineering and Its Applications, 10(2), 271-278.

[6] Cloud Security Alliance. (2014). Retrieved on July 8 from https://cloudsecurityalliance.org

[7] Crampton J, Martin K, Wild P. (2006). On key assignment for hierarchical access control. In Proceedings of 19th Computer Security Foundations Workshop, 98–111.

[8] European Commission. (2012). Commission Proposes a Comprehensive Reform of the Data Protection Rules. Retrieved on July 10 from


[9] European Commission. (2014). Article 29 Data Protection Working Party, Opinion 02/2014 on a referential for requirements for Binding Corporate Rules. Retrieved on July 10 from

http://ec.europa.eu/justice/data-protection/article- 29/documentation/opinion-recommendation/files/2014/wp212_en.pdf

[10] European Union. (2016). Directive 95/46/EC of the European Parliament and of the Council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data. Off J Eur Union, L 281 (1995, November), 0031–0050. Retrieved on July 8 from


[11] De la Torre-Díez I, Lopez-Coronado M, Garcia-Zapirain Soto B, Mendez-Zorrilla A. (2015). Secure Cloud-Based Solutions for Different eHealth Services in Spanish Rural Health Centers. Journal of Medical Internet Research, 17(7), e157.

[12] Fabiano E, Seo M, Wu X, Douglas C. (2015). OpenDBDDAS Toolkit: Secure MapReduce and Hadoop-like Systems. Procedia Computer Science, 51, 1675–1684.

[13] Hingwe K, Bhanu M. (2014). Two Layered Protection for Sensitive Data in Cloud. International Conference on Advances in Computing,Communications and Informatics (ICACCI), 1265-1272.

[14] Hsu C, Zeng B, Zhang M. (2014). A novel group key transfer for big data security. Applied Mathematics and Computation, 249, 436–443.

[15] Jing P. (2014). A New Model of Data Protection on Cloud Storage. Journal of Networks, 9(3), 666-671.

[16] Liu C, Yang C, Zhang X, Chen J. (2015). External integrity verification for outsourced big data in cloud and IoT: A big picture. Future Generation Computer Systems, 49, 58–67.

[17] Lobato de Faria P, Valente Cordeiro J. (2014). Health data privacy and confidentiality rights: Crisis or redemption?. Revista Portuguesa de Saúde Pública, 32(2), 123-133.

[18] Martínez-Pérez, Borja. et al. (2015). Privacy and Security in Mobile Health Apps: A Review and Recommendations. Journal of Medical Systems, 39(1), 181.

[19] Moseley, Edward T. et al. (2014). Journal of Medical Internet Research, 16(11), e259.

[20] Shaikh, Abdul R. et al. (2014). Collaborative Biomedicine in the Age of Big Data: The Case of Cancer. Journal of Medical Internet Research, 16(4), e101.

[21] Subashini S, Kavitha V. (2011) A Metadata Based Storage Model For Securing Data In Cloud Environment. International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, 429-434.

[22] The White House. (2014). President’s Council of Advisors on Science & Technology, Big Data and Privacy: A Technological Perspective, May 1, 2014.

[23] Thilakanathan D, Zhao Y, Chen S, Nepal S, Calvo R, Pardo A. (2014). Protecting and Analysing Health Care Data on Cloud. Second International Conference on Advanced Cloud and Big Data, 143-149.

[24] Yan Z, Ding W, Niemic V, Vasilakos A. (2016). Two Schemes of Privacy-Preserving Trust Evaluation. Future Generation Computer Systems, 62, 175-189.

[25] Zhou G, Zhang D, Liu Y, Yuan Y, Liu Q; A novel image encryption algorithm based on chaos and Line map. (2015). Neurocomputing, 169, 150–157.



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