Abstract
Rapid digitization of medical records and administrative databases, combined with developments in statistics and computing power, promises to make epidemiological research for bettering healthcare more fruitful than ever before. The requirement for access to a copious amount of potentially sensitive patient health information is common in such circumstances (protected health information, such as names, record numbers, addresses, and medication). Such digitalization can also lead to a potential risk for patient confidentiality if a data leak occurs. Keeping the fact in mind, certain methods are being adopted by many organizations to curb such problems. One of the major techniques involved is encryption. In this chapter, we are going to reflect how protected health information (PHI) can be protected with the help of various encryption techniques. It also covers strategies for securing information and maintaining data integrity, as well as the relationship between patient data, measurement data, and diagnosis. This study ends by concluding how far this technique has been helpful in protecting healthcare data, its advantages over other techniques, and its current presence in the system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
DesRoches, C., Campbell, Rao, E, S., Donelan, K., Ferris, T., Jha, A., Kaushal, R., Levy, D., Rosenbaum, S., & Shields, A., (2008). Electronic health records in ambulatory care—A national survey of physicians. New England Journal of Medicine, 359(1), 50–60. https://doi.org/10.1056/NEJMsa0802005
Eichelberg, M., Aden, T., Riesmeier, J., Dogac, A., & Laleci, G. (2005). A survey and analysis of electronic healthcare record standards. ACM Computing Surveys (CSUR), 37(4), 277–315. https://doi.org/10.1145/1118890.1118891
Vimercati, S. D. C., Foresti, S., Jajodia, S., Paraboschi, S., & Samarati, P. (2007). Over-encryption: Management of access control evolution on outsourced data. In Proceedings of the 33rd International Conference on Very Large Databases VLDB ’07 (pp. 123–134).
Benaloh, J., Chase, M., Horvitz, E., & Lauter, K. (2009). Patient controlled encryption: Ensuring privacy of electronic medical records. In Proceedings of the 2009 ACM Workshop on Cloud Computing Security CCSW’09 (pp. 103–114). https://doi.org/10.1145/1655008.1655024
Zhang, G., Liu, X., & Yang, Y. (2015). Time-series pattern based effective noise generation for privacy protection on cloud. IEEE Transactions on Computers, 64(5), 1456–1469. https://doi.org/10.1109/TC.2014.2298013
Silva, B. M., Rodrigues Joel, J. P. C., Canelo, F., Lopes, I. C., & Zhou, L. (2013). A data encryption solution for mobile health apps in cooperation environments. Journal of Medical Internet Research, 15(4), e66. https://doi.org/10.2196/jmir.2498. https://www.jmir.org/2013/4/e66/
Tran, D. H., Hai-Long. N., Wei, Z., & Keong, N. W. (2011). Towards security in sharing data on cloud-based social networks. In 8th International Conference on Information, Communications and Signal Processing (ICICS), Singapore, 2011 (pp. 1–5).
Huda, M., Sonehara, N., & Yamada, S. (2009). A privacy management architecture for patient-controlled personal health record system. Journal of Engineering Science an Technology, 4(2), 154170.
Thilakanathan, D., Chen, S., Nepal, S., Calvo, R., & Alem, L. (2014). A platform for secure monitoring and sharing of generic health data in the Cloud. Future Generation Computer Systems, 35, 102–113. https://doi.org/10.1016/j.future.2013.09.011
Karvelas, P. (2014). The Australian [May 26, 2015]. Australia's mental health system must become more efficient. http://www.theaustralian.com.au/national-affairs/policy/australias-mental-health-system-must-become-more-efficient/story-fn59nokw-1226850819260
Li, W., Ni, W., & Liu, D. (2017). Fine-grained access control for personal health records in cloud computing (pp. 1278–1289). IEEE.
Saleem, S., Ullah, S., & Kwak, K. S. (2011). A study of IEEE 802.15.4 security framework for wireless body area networks. Sensors, 11(2), 1383–1395.
Kumar, P., & Lee, H.-J. (2011). Security issues in healthcare applications using wireless medical sensor networks: A survey. Sensors, 12(1), 55–91.
Gupta, L. (2014). ‘Security in low energy body area networks for healthcare. In Conference Proceedings.
Lovelit Jose, C. M., & Poovammmal, E. (2016). A survey on privacy preservation of healthcare data using cryptographic techniques. International Journal of Pharmacy & Technology, 8(4), 22322.
Rath, M., & Mishra, S. (2019). Advanced-level security in network and real-time applications using machine learning approaches. In Machine learning and cognitive science applications in cyber security (pp. 84–104). IGI Global.
Mishra, S., Sahoo, S., & Mishra, B. K. (2019). Addressing security issues and standards in Internet of things. In Emerging trends and applications in cognitive computing (pp. 224–257). IGI Global.
Kekgathetse, M. (2015). An evaluation of current computing research aimed at improving online security: Encryption.
Mehmood, Z., Ghani, A., Chen, G., & Alghamdi, A. S. (2019). Authentication and secure key management in e-health services: A robust and efficient protocol using biometrics. IEEE Access, 7, 113385–113397. [CrossRef]
Khezr, S., Yassine, M. A., & Benlamri, R. (2019). Blockchain technology in healthcare: A comprehensive review and directions for future research. Applied Sciences, 9, 1736. [CrossRef]
Mishra, S., Tripathy, N., Mishra, B. K., & Mahanty, C. (2019). Analysis of security issues in cloud environment. Security designs for the cloud, IoT, and social networking (pp. 19–41).
Li, H., Yang, Y., Dai, Y., Yu, S., & Xiang, Y. (2020). Achieving secure and efficient dynamic searchable symmetric encryption over medical cloud data. IEEE Transactions on Cloud Computing, 8, 484–494.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Abhishek, Tripathy, H.K., Mishra, S. (2022). A Succinct Analytical Study of the Usability of Encryption Methods in Healthcare Data Security. In: Tripathy, B.K., Lingras, P., Kar, A.K., Chowdhary, C.L. (eds) Next Generation Healthcare Informatics. Studies in Computational Intelligence, vol 1039. Springer, Singapore. https://doi.org/10.1007/978-981-19-2416-3_7
Download citation
DOI: https://doi.org/10.1007/978-981-19-2416-3_7
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-2415-6
Online ISBN: 978-981-19-2416-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)