Privacy-preserving aware data aggregation for IoT-based healthcare with green computing technologies. (July 2022)
- Record Type:
- Journal Article
- Title:
- Privacy-preserving aware data aggregation for IoT-based healthcare with green computing technologies. (July 2022)
- Main Title:
- Privacy-preserving aware data aggregation for IoT-based healthcare with green computing technologies
- Authors:
- Othman, Soufiene Ben
Almalki, Faris A.
Chakraborty, Chinmay
Sakli, Hedi - Abstract:
- Abstract: Despite the rapid development of the Internet of Things technologies where more and more medical sensors and gadgets are connected to the Internet, limited energy resources due to transmission, and security are still main challenges. Most cases, patients wear multiple medical devices that transmit sensed medical data wirelessly to servers, which might cause big traffic on the communication networks, which in turn cause high energy consumption. Therefore, using the data aggregation, we can considerably reduce the energy consumption by eliminating redundant data; yet collected data must be fully protected. 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. For this reason, massive security measures should be taken to ensure that patients' data can only be accessed by legitimate users. This paper proposes EPPADA: Efficient Privacy‑Preserving Authentication and Data Aggregation scheme in conjunction with Homomorphic Encryption concepts to meet requirements of healthcare using IoT with green computing technologies. 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 E-health sensor shield V2.0 platform. Based on securityAbstract: Despite the rapid development of the Internet of Things technologies where more and more medical sensors and gadgets are connected to the Internet, limited energy resources due to transmission, and security are still main challenges. Most cases, patients wear multiple medical devices that transmit sensed medical data wirelessly to servers, which might cause big traffic on the communication networks, which in turn cause high energy consumption. Therefore, using the data aggregation, we can considerably reduce the energy consumption by eliminating redundant data; yet collected data must be fully protected. 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. For this reason, massive security measures should be taken to ensure that patients' data can only be accessed by legitimate users. This paper proposes EPPADA: Efficient Privacy‑Preserving Authentication and Data Aggregation scheme in conjunction with Homomorphic Encryption concepts to meet requirements of healthcare using IoT with green computing technologies. 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 E-health sensor shield V2.0 platform. Based on security analysis that has the most extensive set of security features, our multi-objective approach enhances the End-to-End Delay, Computational Cost, Communication Overhead, besides maintaining security features. … (more)
- Is Part Of:
- Computers & electrical engineering. Volume 101(2022)
- Journal:
- Computers & electrical engineering
- Issue:
- Volume 101(2022)
- Issue Display:
- Volume 101, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 101
- Issue:
- 2022
- Issue Sort Value:
- 2022-0101-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-07
- Subjects:
- Internet of Thing -- Healthcare -- Data aggregation -- Dual-prediction -- Authentication -- Security
Computer engineering -- Periodicals
Electrical engineering -- Periodicals
Electrical engineering -- Data processing -- Periodicals
Ordinateurs -- Conception et construction -- Périodiques
Électrotechnique -- Périodiques
Électrotechnique -- Informatique -- Périodiques
Computer engineering
Electrical engineering
Electrical engineering -- Data processing
Periodicals
Electronic journals
621.302854 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00457906/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compeleceng.2022.108025 ↗
- Languages:
- English
- ISSNs:
- 0045-7906
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.680000
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