Contextual fully homomorphic encryption schemes-based privacy preserving framework for securing fog-assisted healthcare data exchanging applications

The collection of pervasive data from e-healthcare system inherits potential medical significance through the mode of data exchange with the service providers of professional health care. The sensitive data exchange between the health care providers need to satisfy the requirements of user privacy, since the environment of fog computing is highly vulnerable due to the injection of false data from the hybrid IoT devices. However, sharing health data introduces a diversified number of security issues that include privacy leakage and access control with the further possibility of facing crucial challenges for attaining significant data investigation and services. In this paper, a contextual fully homomorphic encryption techniques-based privacy preserving framework (CFHET-PPF) for securing fog-assisted health data exchanging applications. This proposed CFHET-PPF framework integrates three significant fully homomorphic encryption approaches together in preventing false data injection. It is proposed for facilitating the fog nodes to categorize the shared data based on disease risks for indispensable health data analysis. It aids in achieving a maximum reduction in the number of encryptions by offloading a part of storage and computation burden at the side of the patients to the fog nodes. The security investigations of the proposed CFHET-PPF framework confirmed its superiority in fine grained access control, lightweight process and confidentiality with collusion resistance. © 2021, Bharati Vidyapeeth's Institute of Computer Applications and Management.