Secure and privacy preserving predictive framework for iot based health cloud system using cryptographic modfels

The Internet of Things (IoT) is one of the most well-liked developing technologies in the IT sector these days. The Internet of Things is defined as a network of physical objects that are intelligent and connected. Through the use of wired or wireless networks, sensors are integrated into physically connected objects and communicate with one another. The interconnectedness, intelligence, dynamic nature, sensing, large scale, heterogeneity, and security of the Internet of Things are its salient characteristics. A consumer can access a variety of cloud services, including database, application, and storage, through a network. The Internet of Things (IoT) provides a wide range of field applications for ongoing monitoring in many industries, including healthcare. Numerous studies are conducted to guarantee patient data privacy. Another challenging component of health systems is the use of patient data from IoT devices to predict disease. Protecting confidential information from unauthorised access is necessary to increase its security. To improve cloud data privacy, many classical cryptographic algorithms have been applied. Nevertheless, some issues with data privacy persist due to its inadequate security. As a result, this paper suggests an innovative method to protect cloud data privacy. The suggested EGEC encryption system can be used by the users who possess the data to decrypt data like addition and multiplication are carried out.

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Publication Details

Journal
Health Leadership and Quality of Life
Published
2024-12-30
DOI
https://doi.org/10.56294/hl2024.177
Citations
1
Primary Topic
Internet of Things and AI
Type
article
Field-Weighted Citation Impact
0.78
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article

Secure and privacy preserving predictive framework for iot based health cloud system using cryptographic modfels

Nodira Tursunova, S. Davlatov, Nadira Mirametova, Navruzbek Qurbonov et al.
1 citations
Health Leadership and Quality of Life
Internet of Things and AI
0.78
article

Secure and privacy preserving predictive framework for iot based health cloud system using cryptographic modfels

Nodira Tursunova, S. Davlatov, Nadira Mirametova, Navruzbek Qurbonov, Aziza Yunusova, Raʼno Narbekova, Akhmadjon Abdumaruf
article en
1 citations

Abstract

The Internet of Things (IoT) is one of the most well-liked developing technologies in the IT sector these days. The Internet of Things is defined as a network of physical objects that are intelligent and connected. Through the use of wired or wireless networks, sensors are integrated into physically connected objects and communicate with one another. The interconnectedness, intelligence, dynamic nature, sensing, large scale, heterogeneity, and security of the Internet of Things are its salient characteristics. A consumer can access a variety of cloud services, including database, application, and storage, through a network. The Internet of Things (IoT) provides a wide range of field applications for ongoing monitoring in many industries, including healthcare. Numerous studies are conducted to guarantee patient data privacy. Another challenging component of health systems is the use of patient data from IoT devices to predict disease. Protecting confidential information from unauthorised access is necessary to increase its security. To improve cloud data privacy, many classical cryptographic algorithms have been applied. Nevertheless, some issues with data privacy persist due to its inadequate security. As a result, this paper suggests an innovative method to protect cloud data privacy. The suggested EGEC encryption system can be used by the users who possess the data to decrypt data like addition and multiplication are carried out.

Health Leadership and Quality of LifeVol. 3
Ferghana Polytechnical Institute (UZ), Bukhara State Medical Institute named after Abu Ali ibn Sino (UZ), Nukus State Pedagogical Institute named after Ajiniyaz (UZ), Samarkand State Medical Institute (UZ), Jizzakh State Pedagogical University (UZ), Tashkent Medical Academy (UZ)
Openalex Percentile: Top 17%
Internet of Things and AI
0.78
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