Residual LSTM to Execute Access Control Procedure in Blockchain and Data Integrity Through Proxy Re-Encryption Using Elliptical Curve Cryptography

The widespread of cloud storage presents various obstacles in guaranteeing the integrity of the user's private information. The main intent of the multi-cloud storage networks is to improve their integrity. Yet, they are sensitive to the replacement threats. These threats comprise malicious users that replace the authenticated information with fake information that influences the integrity and leads to false audit results. However, numerous difficulties have occurred due to the selection of individual delegators and centralized access control. Hence, to tackle several complications in the existing technique, a novel framework is designed using deep learning and encryption techniques. The novelty of the developed model is to execute an access control procedure in blockchain and data integrity through proxy re-encryption using elliptical curve cryptography. In the developed framework, access control procedures for the Blockchain are executed using Residual Long Short-Term Memory (Res-LSTM), which helps to identify the user's permission in particular resources. Executing user access control procedures helps to recognize malicious users by verifying the user's log information. Next, data integrity in the access control data is verified by performing Proxy Re-Encryption (PRE) using Elliptical Curve Cryptography (ECC). Executing PRE helps to offer secured data sharing with data management and also it eliminates the risks obtained from unauthorized access. Finally, the secured access control outcomes are attained with data integrity. Later, various performance metrics are considered for verifying the performance of the suggested network over the standard approaches.