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LSDA: Lightweight Secure Data Aggregation Scheme in Healthcare using IoT

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Published:22 March 2021Publication History

ABSTRACT

The Internet of Things (IoT) is one of the most promising technologies for the near future. Healthcare and well-being will receive great benefits with the evolution of this technology. For example, the communicating objects can be body sensors, which enable a continuous real-time monitoring of vital information patients. However, due to the direct involvement to patient health information, the privacy and integrity of medical data have become a matter of much concern to the healthcare applications. In this paper, we propose the Lightweight Secure Data Aggregation (LSDA) Scheme, which is a novel secure data aggregation scheme for Healthcare using IoT. This new scheme is characterized by employing the homomorphic encryption. Also, each aggregator needs to verify all packets received from its member nodes, which can filter bogus packets in-network and thus the nodes can save energy on transmission phase. The security analysis and experimental results show that our proposed scheme guarantees patients privacy, messages authenticity, and integrity with lightweight efficiency in terms of communication overheads.

References

  1. Kavyas, Vidyashree," A Survey of Internet of Things (IoT) - Applications, Merits & Challenges", International Journal of Innovative Research in Computer and Communication Engineering, Vol. 6, Issue 2, February 2018Google ScholarGoogle Scholar
  2. Jin-Xin Hu & al, "An Intelligent and Secure Health Monitoring Scheme Using IoT Sensor Based on Cloud Computing", Journal of Sensors, Volume 2017, Article ID 3734764, 2017.Google ScholarGoogle Scholar
  3. Bogdan Cosmin Chifor& al, "A security authorization scheme for smart home Internet of Things devices", Future Generation Computer Systems Volume 86, Pages 740--749, September 2018.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. P. P. Ray, "A survey on Internet of Things architectures", Journal of King Saud University - Computer and Information Sciences Volume 30, Issue 3, Pages 291--319, July 2018.Google ScholarGoogle ScholarCross RefCross Ref
  5. PallaviSethi and Smruti R. Sarangi, "Internet of Things: Architectures, Protocols, and Applications", Journal of Electrical and Computer Engineering, Volume 2017, Article ID 9324035, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Sunday Oyinlola Ogundoyin & Sunday Oladele Awoyemi, "EDAS: Efficient Data Aggregation Scheme for Internet of Things", Journal of Applied Security Research, Volume 13, NO. 3, page 347--375, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  7. Cheng Huang et al, "Reliable and Privacy-Preserving Selective Data Aggregation for Fog-Based IoT", IEEE International Conference on Communications, Kansas City, MO, USA, May 20--24, 2018.Google ScholarGoogle Scholar
  8. S. B. Othman, A. A. Bahattab, A. Trad, H. Youssef, Confidentiality and integrity for data aggregation in WSN using homomorphic encryption, Wireless Personal Communications, volume 80, issue 2, pp 867--889. 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. S. Ben Othman, A. A. Bahattab, A. Trad, H. Youssef, "Lightweight and confidential data aggregation in healthcare wireless sensor networks", Transactions on Emerging Telecommunications Technologies. Volume 27, Issue 1, pp 576--588, 2016.Google ScholarGoogle Scholar
  10. K. Zhang, X. Liang, M. Baura, et al, "PHDA: A priority-based health data aggregation with privacy preservation for cloud assisted WBANs," Information Sciences, Vol. 284, pp. 130--141, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  11. Saleem, K.; Abbas, H.; Al-Muhtadi, J.; Orgun, M.A.; Shankaran, R.; Zhang, G. Empirical Studies of ECG Multiple Fiducial-Points Based Binary Sequence Generation (MFBSG) Algorithm in E-Health Sensor Platform. In Proceedings of the 2016 IEEE 41st Conference on Local Computer Networks Workshops (LCN Workshops), Dubai, United Arab Emirates, 7--10 November 2016; pp. 236--24.Google ScholarGoogle Scholar

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  1. LSDA: Lightweight Secure Data Aggregation Scheme in Healthcare using IoT

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          ICIST '20: Proceedings of the 10th International Conference on Information Systems and Technologies
          June 2020
          292 pages
          ISBN:9781450376556
          DOI:10.1145/3447568

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          Publication History

          • Published: 22 March 2021

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