SECURIG HEALTHCARE DATA IN THE CLOUD AGAINST INFERENCE ATTACKS

Abstract

The E-HealthCare cloud system demonstrates important possibilities for improving healthcare quality  and the well-being of people. However, it has not spread, especially due to the most important concerns about security and privacy. Existing methods for storage rely on basic access control models and are susceptible to inference attacks. In this article, we have set up an inference attack for attacks on e-HealthCare cloud systems that use fine-tuned access controls. We propose a new approach using a two-layer encryption scheme that allows for secure and effective data manipulation. The first encryption layer contains marked access guidelines. This can be tailored to any data attribute where fine access control is achieved and encryption efforts are reduced simultaneously. As a rule, role attributes and access guidelines are hidden within a second encryption layer to protect privacy. The cloud is permitted to perform a variety of mathematically intensive tasks on behalf of the user without disclosing private data, in order to use the computing power of the cloud without affecting the confidentiality of the sensitive information. To achieve this, we develop a blind data access protocol using Paillier encryption. The results of comprehensive security analysis and performance assessments confirm that the proposed solution is as efficient and efficient as a secure cloud management system.