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FC-SEEDA: fog computing-based secure and energy efficient data aggregation scheme for Internet of healthcare Things

  • S.I.: Improving Healthcare outcomes using Multimedia Big Data Analytics
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Abstract

IoT is used in healthcare to monitor patients via wearable sensors to measure different physiological information. This collected information can be stored, processed, and made available to doctors to give a consultation at any time, which improves the efficiency of the traditional medical systems. Secure data collection and transfer to centralized servers in healthcare applications employing IoT is quite challenging to protect against several attacks for illegal data access. Furthermore, the bulk of IoT devices have physical limitations in processing and storage. Securing and effectively aggregating sensitive patient information on the Internet of Healthcare Things remains difficult. This research article proposes FC-SEEDA: Fog Computing-based Secure and Energy-Efficient Data Aggregation scheme for Internet of healthcare Things. By leveraging the distributed nature and other extended capabilities of Fog Computing, the main objective of this proposed scheme is to decrease the communication overhead and energy consumption while maintaining safe and secure aggregation of the healthcare data between medical sensors and cloud servers. The proposed system is experimentally developed using the E-health sensor shield V2.0 platform. Security analysis demonstrates that the proposed aggregation protocol achieves desirable security properties. Performance comparisons show that our newly proposed protocol significantly reduces computing overhead compared to the latest protocols in the field.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, BIT, Mesra, Mesra, Jharkhand, India

    Chinmay Chakraborty

  2. PRINCE Laboratory Research, ISITcom, University of Sousse, Hammam Sousse, Tunisia

    Soufiene Ben Othman

  3. Department of Computer Engineering, College of Computers and Information Technology, Taif University, P.O. Box 11099, 21944, Taif, Kingdom of Saudi Arabia

    Faris A. Almalki

  4. MACS Research Laboratory, National Engineering School of Gabes, Gabes University, 6029, Gabes, Tunisia

    Hedi Sakli

  5. EITA Consulting, 5 Rue du Chant Des Oiseaux, 78360, Montesson, France

    Hedi Sakli

Authors
  1. Chinmay Chakraborty
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  2. Soufiene Ben Othman
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  3. Faris A. Almalki
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  4. Hedi Sakli
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Correspondence to Soufiene Ben Othman.

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Chakraborty, C., Othman, S.B., Almalki, F.A. et al. FC-SEEDA: fog computing-based secure and energy efficient data aggregation scheme for Internet of healthcare Things. Neural Comput & Applic 36, 241–257 (2024). https://doi.org/10.1007/s00521-023-08270-0

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