Protecting the Multimedia using Privacy Preserving Homomorphic Encryption Based Blockchain Model in IoT

Data auditing is becoming increasingly important as more customers want to farm out large programme data produced by Net of Things (IoT) strategy to the cloud. This is because it allows clients to confirm the accuracy of the data they are outsourcing. The majority of current data auditing techniques, however, are unable to ensure complete data integrity and cannot satisfy the security requirements of useful multimedia facilities. Moreover, when the cloud service provider (CSP) tampers with the outsourced data, clients are not promptly compensated due to the lack of fair arbitration. This study suggests a blockchain-based homomorphic encryption-based learning method for multimedia data that protects privacy. In our system, customers often only need to do contract is only triggered to perform a public audit when the private audit's verification is unsuccessful. With this suggested approach, clients may avoid paying audit costs and can be compensated automatically and promptly if the CSP corrupts their outsourced data. Furthermore, when clients want reimbursement from the CSP, our plan can stop bogus claims. We evaluate the security advantages and finish implementing the prototype. The testing findings demonstrate how safe, effective, and useful our blockchain-based data auditing system is.