Publications

@article{Othman2022,

title = {Privacy-preserving aware data aggregation for IoT-based healthcare with green computing technologies},

author = {S. B. Othman and F. A. Almalki and C. Chakraborty and H. Sakli},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129308229\&doi=10.1016%2fj.compeleceng.2022.108025\&partnerID=40\&md5=182a85b26c703ec9fc74b8f18abe32d2},

doi = {10.1016/j.compeleceng.2022.108025},

issn = {00457906},

year  = {2022},

date = {2022-01-01},

journal = {Computers and Electrical Engineering},

volume = {101},

publisher = {Elsevier Ltd},

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 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. © 2022},

note = {cited By 59},

keywords = {Authentication; Energy resources; Energy utilization; Green computing; Health care; Privacy-preserving techniques; Security systems, Communication overheads; Computing technology; Data aggregation; Dual-prediction; Energy-consumption; Internet of things technologies; Medical sensors; Privacy preserving; Security; Security features, Internet of things},

pubstate = {published},

tppubtype = {article}

}