Artificial Intelligence in Cloud Data Integrity Assurance

Cloud computing/cloud storage has emerged as a widely embraced solution to address the escalating storage expenses. faced by IT enterprises. The exorbitant costs associated with data storage devices and the rapid generation of information make it financially burdensome for companies or individual users to update their hardware frequently. In addition to cost reduction, outsourcing data to the cloud contributes to decreased maintenance efforts. Cloud storage enables users to transfer data to expansive data centers situated remotely, over which they have no direct authority or control. While cloud-based data storage is an efficient solution but. introduces new security challenges requiring resolution. The main goal is to develop a procedure that guarantees the integrity of data stored in the cloud, enabling users to confirm that their data has not been tampered with. This proof of integrity is adaptable to both the cloud provider and the customer. Despite the cost-effectiveness of data storage, security remains critical concern. Although various encryption algorithms can enhance security, users cannot guarantee the absolute security of their data. Al, a field that merges computer science with reliable datasets, facilitates efficient problem-solving. Within Al, machine learning and deep learning sub-fields generate specific algorithms. Machine learning and deep learning, being integral to Al, contribute to the development of expert systems that make predictions based on input data. The storage and retrieval of data in the cloud rely on encryption/decryption keys. Instead of generating keys through mathematical functions, biometrics or digital signatures can serve as the key, allowing for encryption/decryption processes.