Blockchain-based cryptographic approach for privacy enabled data integrity model for IoT healthcare

The development of Internet of Things (IoT) technologies allowed the rapid generation of massive amounts of data by people. Although moving data to a server is a useful solution for storage, the owner of the data loses control, which results in security lapses. An efficient method for cloud-based data models is data integrity. In order to protect data privacy in IoT healthcare, this paper develops a data integrity technique. The Data Owner, IoT server, Key Generator Center, and Auditor are the four entities that make up this model. Here, the ability to verify the accuracy of the outsourced data is present in the auditor, data owner, and IoT server. The setup, storage, and verification phase are the three stages that make up the data integrity model. Here, the proposed Taylor-based Border Collie Cat optimisation is used to generate integrity keys in the best possible way. Here, the Taylor series and Border Collie Cat optimisation (BCCO) are combined to derive the proposed Taylor-based BCCO. Python is used to carry out the proposed strategy's implementation. The proposed method offered enhanced performance with highest normalised variance of 0.710, highest conditional privacy of 2.880, and smallest computation time of 0.179 sec using heart disease dataset.