Skip to main content

Advertisement

SpringerLink
Log in

RETRACTED ARTICLE: Medical Data Security for Healthcare Applications Using Hybrid Lightweight Encryption and Swarm Optimization Algorithm

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

This article was retracted on 06 December 2022

This article has been updated

Abstract

In medical field, securing every patient’s record is main concern, ascribed to many fraudulent cases occurring in the health sector. The data of every individual must be engraved and sent into end-user without any issues. Mainly in the healthcare industry, where thoughts are often focused on saving someone’s life and rightly so, but securing access to interfaces and computer systems that store private data like medical records is also an essential factor to consider. Data security is a corresponding action between controlling access to information while allowing free and easy access to those who need that information. Still few problems are focused by the physician in the health sector. Patient’s data should be kept securely in medical provider servers so that physicians can provide proper treatments. To ensure secure storage and access management, we propose a novel hybrid lightweight encryption using swarm optimization algorithm (HLE–SO).The proposed HLE–SO technique merge Paillier encryption and KATAN algorithm, which provides the lightweight features. Generally, the lightweight encryption algorithms are affected by the key space. We introduce the swarm optimization algorithm to optimize the key space by changing the number of iteration round. Our main goal is to encrypt the medical data (EEG signal) and send to end user by utilizing proposed HLE–SO method. Finally, the implementation is done with MATLAB tool with different EEG signal data set. The simulation results of proposed HLE–SO technique is compared with the existing state-of-art techniques in terms of different performance metrics are MSE, PSNR, SSIM, PRD, encryption time and decryption time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Change history

References

  1. Lee, W.-B., & Lee, C.-D. (2008). A cryptographic key management solution for HIPAA privacy/security regulations. IEEE Transactions on Information Technology in Biomedicine, 12(1), 34–41.

    Article  Google Scholar 

  2. Halperin, D., Heydt-Benjamin, T., Fu, K., Kohno, T., & Maisel, W. (2008). Security and privacy for implantable medical devices. IEEE Pervasive Computing, 7(1), 30–39.

    Article  Google Scholar 

  3. Healthcare Editorial Office. (2015). Acknowledgement to reviewers of healthcare in 2014. Healthcare, 3(1), 1–2.

    Article  Google Scholar 

  4. Kahn, S., & Sheshadri, V. (2008). Medical record privacy and security in a digital environment. IT Professional, 10(2), 46–52.

    Article  Google Scholar 

  5. Maglogiannis, I., Kazatzopoulos, L., Delakouridis, K., & Hadjiefthymiades, S. (2009). Enabling location privacy and medical data encryption in patient telemonitoring systems. IEEE Transactions on Information Technology in Biomedicine, 13(6), 946–954.

    Article  Google Scholar 

  6. Kaufman, L. (2009). Data security in the world of cloud computing. IEEE Security and Privacy Magazine, 7(4), 61–64.

    Article  Google Scholar 

  7. Li, M., Lou, W., & Ren, K. (2010). Data security and privacy in wireless body area networks. IEEE Wireless Communications, 17(1), 51–58.

    Article  Google Scholar 

  8. Hu, F., Hao, Q., Lukowiak, M., Sun, Q., Wilhelm, K., Radziszowski, S., et al. (2010). Trustworthy data collection from implantable medical devices via high-speed security implementation based on IEEE 1363. IEEE Transactions on Information Technology in Biomedicine, 14(6), 1397–1404.

    Article  Google Scholar 

  9. Barni, M., Failla, P., Lazzeretti, R., Sadeghi, A., & Schneider, T. (2011). Privacy-preserving ECG classification with branching programs and neural networks. IEEE Transactions on Information Forensics and Security, 6(2), 452–468.

    Article  Google Scholar 

  10. Heckle, R. (2011). Security dilemma: Healthcare clinicians at work. IEEE Security & Privacy Magazine, 9(6), 14–19.

    Article  Google Scholar 

  11. Wang, W., Wang, H., Hempel, M., Peng, D., Sharif, H., & Chen, H. (2011). Secure stochastic ECG signals based on Gaussian mixture model for $e$-healthcare systems. IEEE Systems Journal, 5(4), 564–573.

    Article  Google Scholar 

  12. Charney, S. (2012). Collective defense: Applying the public-health model to the internet. IEEE Security and Privacy Magazine, 10(2), 54–59.

    Article  MathSciNet  Google Scholar 

  13. Ma, T., Shrestha, P., Hempel, M., Peng, D., Sharif, H., & Chen, H.-H. (2012). Assurance of energy efficiency and data security for ECG transmission in BASNs. IEEE Transactions on Biomedical Engineering, 59(4), 1041–1048.

    Article  Google Scholar 

  14. Venkatasubramanian, K., Vasserman, E., Sokolsky, O., & Lee, I. (2012). Security and Interoperable-medical-device systems, Part 1. IEEE Security and Privacy, 10(5), 61–63.

    Article  Google Scholar 

  15. Solanas, A., Martinez-Balleste, A., & Mateo-Sanz, J. (2013). Distributed architecture with double-phase microaggregation for the private sharing of biomedical data in mobile health. IEEE Transactions on Information Forensics and Security, 8(6), 901–910.

    Article  Google Scholar 

  16. Trcek, D., & Brodnik, A. (2013). Hard and soft security provisioning for computationally weak pervasive computing systems in E-health. IEEE Wireless Communications, 20(4), 22–29.

    Article  Google Scholar 

  17. Caine, K., & Lesk, M. (2013). Security and privacy in health IT [Guest editors' introduction]. IEEE Security and Privacy, 11(6), 10–11.

    Article  Google Scholar 

  18. Mitchell, R., & Chen, I. (2015). Behavior rule specification-based intrusion detection for safety critical medical cyber physical systems. IEEE Transactions on Dependable and Secure Computing, 12(1), 16–30.

    Article  Google Scholar 

  19. Simplicio, M., Iwaya, L., Barros, B., Carvalho, T., & Naslund, M. (2015). SecourHealth: A delay-tolerant security framework for mobile health data collection. IEEE Journal of Biomedical and Health Informatics, 19(2), 761–772.

    Article  Google Scholar 

  20. Ma, J., Zhang, T., & Dong, M. (2014). A novel ECG data compression method using adaptive Fourier decomposition with security guarantee in e-Health applications. IEEE Journal of Biomedical and Health Informatics, 19(3), 1–1.

    Google Scholar 

  21. Xiong, H., Tao, J., & Yuan, C. (2017). Enabling telecare medical information systems with strong authentication and anonymity. IEEE Access, 5, 1–1.

    Article  Google Scholar 

  22. Ara, A., Al-Rodhaan, M., Tian, Y., & Al-Dhelaan, A. (2017). A secure privacy-preserving data aggregation scheme based on bilinear ElGamal cryptosystem for remote health monitoring systems. IEEE Access, 5, 12601–12617.

    Article  Google Scholar 

  23. Liu, T., Lin, K., & Wu, H. (2018). ECG data encryption then compression using singular value decomposition. IEEE Journal of Biomedical and Health Informatics, 22(3), 707–713.

    Article  Google Scholar 

  24. Shehab, A., Elhoseny, M., Muhammad, K., Sangaiah, A., Yang, P., Huang, H., et al. (2018). Secure and robust fragile watermarking scheme for medical images. IEEE Access, 6, 10269–10278.

    Article  Google Scholar 

  25. Luo, E., Bhuiyan, M., Wang, G., Rahman, M., Wu, J., & Atiquzzaman, M. (2018). PrivacyProtector: Privacy-protected patient data collection in IoT-based healthcare systems. IEEE Communications Magazine, 56(2), 163–168.

    Article  Google Scholar 

  26. El-Latif, A. A., Abd-El-Atty, B., Hossain, M., Rahman, M., Alamri, A., & Gupta, B. (2018). Efficient quantum information hiding for remote medical image sharing. IEEE Access, 6, 21075–21083.

    Article  Google Scholar 

  27. Yang, W., Wang, S., Hu, J., Zheng, G., Chaudhry, J., Adi, E., et al. (2018). Securing mobile healthcare data: A smart card based cancelable finger-vein bio-cryptosystem. IEEE Access, 6, 36939–36947.

    Article  Google Scholar 

  28. Abbasinezhad-Mood, D., & Nikooghadam, M. (2018). Efficient design of a novel ECC-based public key scheme for medical data protection by utilization of NanoPi fire. IEEE Transactions on Reliability, 67(3), 1328–1339.

    Article  Google Scholar 

  29. Datta, B., Pal, P., & Bandyopadhyay, S. (2018). Audio transmission of medical reports for visa processing: A solution for the spread of communicable diseases by the immigrant population. IEEE Consumer Electronics Magazine, 7(5), 27–33.

    Article  Google Scholar 

  30. Boussif, M., Aloui, N., & Cherif, A. (2018). Secured cloud computing for medical data based on watermarking and encryption. IET Networks, 7(5), 294–298.

    Article  Google Scholar 

  31. Dong, H., Wu, C., Wei, Z., & Guo, Y. (2018). Dropping activation outputs with localized first-layer deep network for enhancing user privacy and data security. IEEE Transactions on Information Forensics and Security, 13(3), 662–670.

    Article  Google Scholar 

  32. Murillo-Escobar, M. A., Cardoza-Avendaño, L., López-Gutiérrez, R. M., & Cruz-Hernández, C. (2017). A double chaotic layer encryption algorithm for clinical signals in telemedicine. Journal of Medical Systems, 41(4), 59.

    Article  Google Scholar 

  33. Kennedy, J. (2011). Particle swarm optimization. Encyclopedia of machine learning (pp. 760–766). New York: Springer.

    Google Scholar 

  34. Shi, Y. (2001). Particle swarm optimization: Developments, applications and resources. In Proceedings of the 2001 Congress on IEEE evolutionary computation

  35. Liu, R., & Lu, C. (2010). On adaptive particle swarm optimization algorithm-AFIPSO. Jisuanji Yingyong yu Ruanjian 27(11).

  36. Feng, L., & Wei, W. (2012). Adaptive particle swarm optimization algorithm and its application. Journal of Software Engineering, 6, 41–48.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Technology, Rajalakshmi Engineering College, Chennai, India

    K. Tamilarasi

  2. Department of Electronics and Communication Engineering, SSN College of Engineering, Chennai, Tamilnadu, India

    A. Jawahar

Authors
  1. K. Tamilarasi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Jawahar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. Tamilarasi.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s11277-022-10120-6

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tamilarasi, K., Jawahar, A. RETRACTED ARTICLE: Medical Data Security for Healthcare Applications Using Hybrid Lightweight Encryption and Swarm Optimization Algorithm. Wireless Pers Commun 114, 1865–1886 (2020). https://doi.org/10.1007/s11277-020-07229-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-020-07229-x

Keywords

Search

Navigation