Smart health system with deep kronecker network-based key generation for privacy-aware aggregate authentication and access control in IoT

M. Sathya, V. Mareeswari, M. Jeyaselvi () and A. Solairaj
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M. Sathya: Nadar Saraswathi College of Engineering and Technology
V. Mareeswari: AMC Engineering College
M. Jeyaselvi: SRM Institute of Science and Technology
A. Solairaj: Sethu Institute of Technology

Journal of Combinatorial Optimization, 2025, vol. 49, issue 5, No 13, 26 pages

Abstract: Abstract The Internet of Things (IoT) application is an application and service that incorporates both the physical and information world. Similarly, it is difficult for existing health systems to provide privacy-aware aggregate authentication and fine-grained access control. To bridge the concern, a smart health system (SHS) with Deep Kronecker Network_key generation (DKN_keyGen) for privacy-aware aggregate authentication and access control in IoT is implemented. Here, entities employed for this model such as data owner (DO), registration center (RC), data user (DU) and cloud service provider (CSP). The method follows four steps, such as system initialization, user registration, Health data outsourcing and Health data access. Initially, the RC needs to initialize the security parameters, random parameters and public keys. After that, DO and DU must be registered in RC. Moreover, the smart health care data of DO generates the secret parameter and also obtains the secret parameter from the RC. The cloud storage stores and manages health care data in the health data outsourcing step. Finally, for health data access, the user gives appropriate parameters and access to the data which is implemented in the data access phase. The model is established considering different security functionalities including Encryption, ECC, XoR and hashing function. Here, the key is generated using DKN. The proposed model obtained a minimum computation time of 6.857 s, memory usage of 30 MB, and communication cost of 20.

Keywords: Internet of Things (IoT); Smart health system; Access control; Deep learning (DL); Deep Kronecker Network (DKN) (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10878-025-01303-5

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