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Privacy Preservation of Electronic Health Record: Current Status and Future Direction

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Handbook of Computer Networks and Cyber Security

Abstract

Recent developments in health sector have made it possible to collect, store, manage, and share medical data in large scale. Managing and sharing of health record is primarily requirement in electronic health record software, however, reusability of electronic health records in distributive environment or access by third party must maintain principle of database system and implement the guidelines of international privacy policy standards and regulations. Privacy preservation is the major concern while dealing with real-time datasets in health sector. Privacy preservation algorithms have to ensure protection of sensitive information related to patients’ diagnoses and diseases. Privacy preserving data mining (PPDM) deals with data perturbation, anonymities, and modification as per the requirement of the system. Data perturbation is one of best PPDM techniques that basically deals with numeric values and focuses on privacy implementation. In this chapter, we will select and review different articles that are related to electronic health records (EHRs), their privacy standards, challenges, and regulations currently adopted in different countries. This chapter mainly reviews the current status of privacy preservation polices used in EHR, privacy techniques and analysis, and future scope of privacy in global scenario.

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References

  1. Bos, J. W., Lauter, K., & Naehrig, M. (2014). Private predictive analysis on encrypted medical data. Journal of Biomedical Informatics, 50, 234–243.

    Article  Google Scholar 

  2. Li, M., Yu, S., Ren, K., & Lou, W. (2010, September). Securing personal health records in cloud computing: Patient-centric and fine-grained data access control in multi-owner settings. In International Conference on Security and Privacy in Communication Systems (pp. 89–106). Berlin: Springer.

    Google Scholar 

  3. Fan, L., Buchanan, W., Thummler, C., Lo, O., Khedim, A., Uthmani, O., & Bell, D. (2011, July). DACAR platform for eHealth services cloud. In Cloud Computing (CLOUD), 2011 IEEE International Conference on (pp. 219–226). Los Alamitos: IEEE.

    Chapter  Google Scholar 

  4. Squicciarini, A. C., Hintoglu, A. A., Bertino, E., & Saygin, Y. (2007, June). A privacy preserving assertion based policy language for federation systems. In Proceedings of the 12th ACM Symposium on Access Control Models and Technologies (pp. 51–60). New York: ACM.

    Google Scholar 

  5. Jurczyk, P., & Xiong, L. (2009). Distributed anonymization: Achieving privacy for both data subjects and data providers. In E. Gudes & J. Vaidya (Eds.), Data and applications security XXIII. DBSec 2009 (Lecture notes in computer science) (Vol. 5645). Berlin: Springer.

    Google Scholar 

  6. Abbas, A., & Khan, S. U. (2014). A review on the state-of-the-art privacy-preserving approaches in the e-health clouds. IEEE Journal of Biomedical and Health Informatics, 18(4), 1431–1441.

    Article  Google Scholar 

  7. Goldman, J., & Hudson, Z. (2000). Virtual exposed: Privacy and eHealth. Health Affairs, 19, 140–148.

    Article  Google Scholar 

  8. Clifton, C., & Anandan, B. (2013, December). Challenges and opportunities for security with differential privacy. In International Conference on Information Systems Security (pp. 1–13). Berlin: Springer.

    Google Scholar 

  9. Mohammed, N., Chen, R., Fung, B., & Yu, P. S. (2011, August). Differentially private data release for data mining. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 493–501). New York: ACM.

    Chapter  Google Scholar 

  10. Pommerening, K., & Reng, M. (2004). Secondary use of the EHR via pseudonymization. In Medical care compunetics on system sciences (pp. 441–446). Amsterdam: IOS Press.

    Google Scholar 

  11. Li, M., Yu, S., Ren, K., & Lou, W. (2010). Securing personal health records in cloud computing: Patient-centric and fine-grained data access control in multi-owner settings. In S. Jajodia & J. Zhou (Eds.), Security and Privacy in Communication Networks. SecureComm 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (Vol. 50). Berlin: Springer.

    Google Scholar 

  12. Chen, T. S., Liu, C. H., Chen, T. L., Chen, C. S., Bau, J. G., & Lin, T. C. (2012). Secure dynamic access control scheme of PHR in cloud computing. Journal of Medical Systems, 36(6), 4005–4020.

    Article  Google Scholar 

  13. Zhang, R., Liu, L., & Xue, R. (2013). Role – Based and time bound access and management of HER data. Security and communication Networks, 7(6), 994–1015.

    Article  Google Scholar 

  14. Ueckert, F., & Prokosch, H. U. (2002). Implementing security and access control mechanism for an healthcare record. In Proceedings of the AMIA Symposium (pp. 825–829). Bethesda: American Medical Informatics Association.

    Google Scholar 

  15. Hu, J., Chen, H. H., & Hou, T. W. (2010). A hybrid public key infrastructure solution (HPKI) for HIPAA privacy/security regulations. Computer Standards & Interface, 32(5–6), 274–280.

    Article  Google Scholar 

  16. Jafari, M., Safavi-Naini, R., Saunders, C., & Sheppard, N. P. (2010). Using digital rights management for securing data in a medical research environment. In Proceedings of the Tenth Annual ACM Workshop on Digital Rights Management (pp. 55–60). New York: ACM.

    Chapter  Google Scholar 

  17. Rothstein, M. A. (2007). Health privacy in the electronic age. The Journal of Legal Medicine, 28(4), 487–501.

    Article  Google Scholar 

  18. Farzandipour, M., Sadought, F., Ahmadi, M., & Karimi, I. (2010). Security requirement and solutions in electronic health record: Lessons learned from a comparative study. Journal of Medical Systems, 34(4), 629–642.

    Article  Google Scholar 

  19. Aggarwal, C. C., & Philip, S. Y. (2008). A general survey of privacy-preserving data mining models and algorithms. In Privacy-preserving data mining (pp. 11–52). Boston: Springer.

    Chapter  Google Scholar 

  20. Sweeney, L. (2002). K-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(05), 557–570.

    Article  MathSciNet  MATH  Google Scholar 

  21. Martínez, S., Sánchez, D., & Valls, A. (2013). A semantic framework to protect the privacy of electronic health records with non-numerical attributes. Journal of Biomedical Informatics, 46(2), 294–303.

    Article  Google Scholar 

  22. Fernández-Alemán, J. L., Señor, I. C., Lozoya, P. Á. O., & Toval, A. (2013). Security and privacy in electronic health records: A systematic literature review. Journal of Biomedical Informatics, 46(3), 541–562.

    Article  Google Scholar 

  23. Ghazvini, A., & Shukur, Z. (2013). Security challenges and success factors of electronic healthcare system. Procedia Technology, 11, 212–219.

    Article  Google Scholar 

  24. Gkoulalas-Divanis, A., Loukides, G., & Sun, J. (2014). Publishing data from electronic health records while preserving privacy: A survey of algorithms. Journal of Biomedical Informatics, 50, 4–19.

    Article  Google Scholar 

  25. Wang, H., Wu, Q., Qin, B., & Domingo-Ferrer, J. (2014). FRR: Fair remote retrieval of outsourced private medical records in electronic health networks. Journal of Biomedical Informatics, 50, 226–233.

    Article  Google Scholar 

  26. Deleger, L., Lingren, T., Ni, Y., Kaiser, M., Stouten borough, L., Marsolo, K., & Solti, I. (2014). Preparing an annotated gold standard corpus to share with extramural investigators for de-identification research. Journal of Biomedical Informatics, 50, 173–183.

    Article  Google Scholar 

  27. Randall, S. M., Ferrante, A. M., Boyd, J. H., Bauer, J. K., & Semmens, J. B. (2014). Privacy-preserving record linkage on large real world datasets. Journal of Biomedical Informatics, 50, 205–212.

    Article  Google Scholar 

  28. Loukides, G., Liagouris, J., Gkoulalas-Divanis, A., & Terrovitis, M. (2014). Disassociation for electronic health record privacy. Journal of Biomedical Informatics, 50, 46–61.

    Article  Google Scholar 

  29. Sánchez, D., Batet, M., & Viejo, A. (2014). Utility-preserving privacy protection of textual healthcare documents. Journal of Biomedical Informatics, 52, 189–198.

    Article  Google Scholar 

  30. Fu, A. W. C., Wang, K., Wong, R. C. W., Wang, J., & Jiang, M. (2014). Small sum privacy and large sum utility in data publishing. Journal of Biomedical Informatics, 50, 20–31.

    Article  Google Scholar 

  31. Meystre, S. M., Ferrández, Ó., Friedlin, F. J., South, B. R., Shen, S., & Samore, M. H. (2014). Text de-identification for privacy protection: A study of its impact on clinical text information content. Journal of Biomedical Informatics, 50, 142–150.

    Article  Google Scholar 

  32. Yu, F., Fienberg, S. E., Slavković, A. B., & Uhler, C. (2014). Scalable privacy-preserving data sharing methodology for genome-wide association studies. Journal of Biomedical Informatics, 50, 133–141.

    Article  Google Scholar 

  33. Gursoy, M. E., Inan, A., Nergiz, M. E., & Saygin, Y. (2017). Privacy-preserving learning analytics: Challenges and techniques. IEEE Transactions on Learning Technologies, 10(1), 68–81.

    Article  Google Scholar 

  34. Mendes, R., & Vilela, J. P. (2017). Privacy-preserving data mining: Methods, metrics, and applications. IEEE Access, 5, 10562–10582.

    Article  Google Scholar 

  35. Majeed, A. (2018). Attribute-centric anonymization scheme for improving user privacy and utility of publishing e-health data. Journal of King Saud University-Computer and Information Sciences. In press.

    Google Scholar 

  36. Kulkarni, Y. R., & Senthil Murugan, T. (2016). Genetic grey wolf optimization and C-mixture for collaborative data publishing. International Journal of Modeling, Simulation, and Scientific Computing, 9(06), 1850058.

    Article  Google Scholar 

  37. Wang, L. E., & Li, X. (2018). A graph-based multifold model for anonymizing data with attributes of multiple types. Computers & Security, 72, 122–135.

    Article  Google Scholar 

  38. Abouel mehdi, K., Beni-Hessane, A., & Khaloufi, H. (2018). Big healthcare data: Preserving security and privacy. Journal of Big Data, 5(1), 1.

    Article  Google Scholar 

  39. Anjum, A., Choo, K. K. R., Khan, A., Haroon, A., Khan, S., Khan, S. U., & Raza, B. (2018). An efficient privacy mechanism for electronic health records. Computers & Security, 72, 196–211.

    Article  Google Scholar 

  40. Kamateri, E., Kalampokis, E., Tambouris, E., & Tarabanis, K. (2014). The linked medical data access control framework. Journal of Biomedical Informatics, 50, 213–225.

    Article  Google Scholar 

  41. Yu, H., Vaidya, J., & Jiang, X. (2006, April). Privacy-preserving SVM classification on vertically partitioned data. In Pacific-Asia Conference on Knowledge Discovery and Data Mining (pp. 647–656). Berlin: Springer.

    Chapter  Google Scholar 

  42. Brickell, J., & Shmatikov, V. (2008, August). The cost of privacy: Destruction of data-mining utility in anonymized data publishing. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 70–78). New York: ACM.

    Chapter  Google Scholar 

  43. Wang, J., Zhang, Z., Yang, X., Zuo, L., & Kim, J. U. (2013). Data security and privacy of e-healthcare in electronic medical environment (Vol. 22, pp. 92–98). ASTL SIA.

    Google Scholar 

  44. Dong, N., Jonker, H., & Pang, J. (2011, August). Challenges in eHealth: From enabling to enforcing privacy. In International Symposium on Foundations of Health Informatics Engineering and Systems (pp. 195–206). Berlin: Springer.

    Google Scholar 

  45. Lin, H., Shao, J., Zhang, C., & Fang, Y. (2013). CAM: Cloud-assisted privacy preserving mobile health monitoring. IEEE Transactions on Information Forensics and Security, 8(6), 985–997.

    Article  Google Scholar 

  46. Retrieved October 19, 2018, from https://www.thehindu.com/news/resources/supreme-court-verdict-on-right-to-privacy/article19551827.ece

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Author information

Authors and Affiliations

  1. USICT, GGSIPU, Delhi, India

    Anil Kumar

  2. Skill Faculty of Engineering, SVSU, Dudhola Palwal, India

    Ravinder Kumar

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  1. Anil Kumar
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  2. Ravinder Kumar
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Editor information

Editors and Affiliations

  1. Department of Computer Engineering, National Institute of Technology Kurukshetra, Kurukshetra, India

    Brij B. Gupta

  2. Department of Computer Science, University of Murcia, Catedrático de Universidad, Murcia, Spain

    Gregorio Martinez Perez

  3. Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, USA

    Dharma P. Agrawal

  4. LoginRadius Inc., Vancouver, BC, Canada

    Deepak Gupta

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Kumar, A., Kumar, R. (2020). Privacy Preservation of Electronic Health Record: Current Status and Future Direction. In: Gupta, B., Perez, G., Agrawal, D., Gupta, D. (eds) Handbook of Computer Networks and Cyber Security. Springer, Cham. https://doi.org/10.1007/978-3-030-22277-2_28

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  • DOI: https://doi.org/10.1007/978-3-030-22277-2_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22276-5

  • Online ISBN: 978-3-030-22277-2

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