research-article

LSDA: Lightweight Secure Data Aggregation Scheme in Healthcare using IoT

Authors:

Ben Othman Soufiene,

Abdullah Ali Bahattab,

Abdelbasset Trad,

Habib YoussefAuthors Info & Claims

ICIST '20: Proceedings of the 10th International Conference on Information Systems and Technologies

Article No.: 22, Pages 1 - 4

https://doi.org/10.1145/3447568.3448530

Published: 22 March 2021 Publication History

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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.

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Cited By

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Chakraborty COthman SAlmalki FSakli H(2024)FC-SEEDA: fog computing-based secure and energy efficient data aggregation scheme for Internet of healthcare ThingsNeural Computing and Applications10.1007/s00521-023-08270-036:1(241-257)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1007/s00521-023-08270-0
Othman SAlmalki FChakraborty CSakli H(2022)Privacy-preserving aware data aggregation for IoT-based healthcare with green computing technologiesComputers and Electrical Engineering10.1016/j.compeleceng.2022.108025101:COnline publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1016/j.compeleceng.2022.108025
Almalki FSoufiene B(2021)EPPDAWireless Communications & Mobile Computing10.1155/2021/55941592021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/5594159

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LSDA: Lightweight Secure Data Aggregation Scheme in Healthcare using IoT

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- The survey provides a deep discussion on the use of: IoT-based secure healthcare solutions for provisioning prominent healthcare applications.

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Published In

ICIST '20: Proceedings of the 10th International Conference on Information Systems and Technologies

June 2020

292 pages

ISBN:9781450376556

DOI:10.1145/3447568

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 March 2021

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ICIST '20

ICIST '20: 10th International Conference on Information Systems and Technologies

June 4 - 5, 2020

Lecce, Italy

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Chakraborty COthman SAlmalki FSakli H(2024)FC-SEEDA: fog computing-based secure and energy efficient data aggregation scheme for Internet of healthcare ThingsNeural Computing and Applications10.1007/s00521-023-08270-036:1(241-257)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1007/s00521-023-08270-0
Othman SAlmalki FChakraborty CSakli H(2022)Privacy-preserving aware data aggregation for IoT-based healthcare with green computing technologiesComputers and Electrical Engineering10.1016/j.compeleceng.2022.108025101:COnline publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1016/j.compeleceng.2022.108025
Almalki FSoufiene B(2021)EPPDAWireless Communications & Mobile Computing10.1155/2021/55941592021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/5594159

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IoT Applications -- Healthcare and Security Case Study (Fast Abstract)

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

A holistic survey on the use of emerging technologies to provision secure healthcare solutions