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

Davlatov, Qurbonov, Yunusova, Tursunova, Narbekova, Abdumaruf, Mirametova and Omarova

Health Leadership and Quality of Life, 2024, vol. 3, .582

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.

Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:dbk:health:v:3:y:2024:i::p:.582:id:.582

DOI: 10.56294/hl2024.582

Access Statistics for this article

More articles in Health Leadership and Quality of Life from AG Editor
Bibliographic data for series maintained by Javier Gonzalez-Argote ().