Abstract
Cloud computing aims to provide reliable, customized, and quality of service (QoS) guaranteed dynamic computing environments for end-users. However, there are applications such as e-health and emergency response monitoring that require quick response and low latency. Delays caused by transferring data over the cloud can seriously affect the performance and reliability of real-time applications. Before outsourcing e-health care data to the cloud, the user needs to perform encryption on these sensitive data to ensure its confidentiality. Conventionally, any modification to the user data requires encrypting the entire data and calculating the hash of the data from scratch. This data modification mechanism increases communication and computation costs over the cloud. The distributed environment of fog computing is used to overcome the limitations of cloud computing. This paper proposed a certificate-based incremental proxy re-encryption scheme (CB-PReS) for e-health data sharing in fog computing. The proposed scheme improves the file modification operations, i.e., updation, deletion, and insertion. The proposed scheme is tested on the iFogSim simulator. The iFogSim simulator facilitates the development of models for fog and IoT environments, and it also measures the impact of resource management techniques regarding network congestion and latency. Experiments depict that the proposed scheme is better than the existing schemes based on expensive bilinear pairing and elliptic curve techniques. The proposed scheme shows significant improvement in key generation and file modification time.
Highlights
Health monitoring has become a leading issue in modern paradigms all over the world
Hyperelliptic curve (HEC) is a family of public-key cryptosystems, and its structure is based on algebraic curves. at is why, it is called a special class of algebraic curves and can be seen as a generalized form of elliptic curve cryptography (ECC) [65]
To reduce the overhead of resource constraints IoT devices, complex and resource-intensive cryptographic functions are offloaded on fog nodes
Summary
Health monitoring has become a leading issue in modern paradigms all over the world. Readings are collected from the medical devices and shared with the authorized health teams. Ese medical devices generate a large amount of data, and managing those data using traditional hardware or software has become a huge challenge [2, 3]. Since the advent of COVID-19, medical big data (MBD) has become important for the effective health monitoring systems. People suffer from many diseases in the world but Parkinson’s disease (PD) is a serious neurodegenerative disorder. Some recent studies have suggested different techniques for diagnosing Parkinson’s disease [8, 9]. Ese studies have improved the automated Parkinson’s disease detection using neural network techniques Some recent studies have suggested different techniques for diagnosing Parkinson’s disease [8, 9]. ese studies have improved the automated Parkinson’s disease detection using neural network techniques
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