Secure and privacy preserving predictive framework for iot based health cloud system using cryptographic modfels
DOI:
https://doi.org/10.56294/hl2024.177Keywords:
Encryption, decryption, diabetes, machine learningAbstract
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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Copyright (c) 2024 Salim Davlatov, Navruzbek Qurbonov, Aziza Yunusova , Nodira Tursunova, Raʼno Narbekova, Akhmadjon Abdumaruf , Nadira Mirametova (Author)
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