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Article type: Research Article
Authors: Thenmozhi, R.a; * | Sakthivel, P.b | Kulothungan, K.a
Affiliations: [a] Information Science and Technology, College of Engineering Guindy, Anna University, Chennai, India | [b] Electronics and Communication Engineering, College of Engineering Guindy, Anna University, Chennai, India
Correspondence: [*] Corresponding author. R. Thenmozhi, E-mail: rtmozhi86@auist.net.
Abstract: The Internet of Things and Quantum Computing raise concerns, as Quantum IoT defines security that exploits quantum security management in IoT. The security of IoT is a significant concern for ensuring secure communications that must be appropriately protected to address key distribution challenges and ensure high security during data transmission. Therefore, in the critical context of IoT environments, secure data aggregation can provide access privileges for accessing network services. "Most data aggregation schemes achieve high computational efficiency; however, the cryptography mechanism faces challenges in finding a solution for the expected security desecration, especially with the advent of quantum computers utilizing public-key cryptosystems despite these limitations. In this paper, the Secure Data Aggregation using Quantum Key Management scheme, named SDA-QKM, employs public-key encryption to enhance the security level of data aggregation. The proposed system introduces traceability and stability checks for the keys to detect adversaries during the data aggregation process, providing efficient security and reducing authentication costs. Here the performance has been evaluated by comparing it with existing competing schemes in terms of data aggregation. The results demonstrate that SDA-QKM offers a robust security analysis against various threats, protecting privacy, authentication, and computation efficiency at a lower computational cost and communication overhead than existing systems.
Keywords: Internet of things, security, data aggregation, access control, quantum cryptography
DOI: 10.3233/JIFS-223619
Journal: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2024
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