M. Sathya, V. Mareeswari, M. Jeyaselvi, A. Solairaj
{"title":"基于深度kronecker网络的智能健康系统,用于物联网中隐私感知聚合认证和访问控制","authors":"M. Sathya, V. Mareeswari, M. Jeyaselvi, A. Solairaj","doi":"10.1007/s10878-025-01303-5","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"48 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Smart health system with deep kronecker network-based key generation for privacy-aware aggregate authentication and access control in IoT\",\"authors\":\"M. Sathya, V. Mareeswari, M. Jeyaselvi, A. Solairaj\",\"doi\":\"10.1007/s10878-025-01303-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":50231,\"journal\":{\"name\":\"Journal of Combinatorial Optimization\",\"volume\":\"48 1\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2025-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Combinatorial Optimization\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s10878-025-01303-5\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Combinatorial Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10878-025-01303-5","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Smart health system with deep kronecker network-based key generation for privacy-aware aggregate authentication and access control in IoT
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.
期刊介绍:
The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering.
The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.