Healthcare Data Security in Multi-Cloud Infrastructure Using Heuristic Algorithms

Due to the large amount of healthcare data that are accumulated and the information that is maintained in cloud premises, it is now essential to secure medical data in cloud environments. The focus is on using a lightweight approach to safely store patient data on the cloud. In the rapidly evolving landscape of multi-cloud infrastructure, safeguarding sensitive information remains a critical concern. This study delves into the domain of multi-cloud infrastructure and its implications for cyber security. The study introduces a novel approach rooted in a semantically grounded data splitting mechanism. This mechanism effectively identifies segments of data vulnerable to cyber security risks and strategically divides them, ensuring that each portion remains shielded from potential threats. Leveraging the distributed storage capabilities of multi-cloud environments, this technique safeguards the sensitive information from external entities. The proposed cyber security model employs heuristic algorithms to optimize the allocation of cloud storage, minimizing the footprint required for data protection. To demonstrate the feasibility and generality of this approach, the study focuses on unstructured data in the form of plain textual documents. Homomorphic encryption is employed to enable secure computation on cipher texts, further enhancing data confidentiality. The re-encryption process inherent in homomorphic encryption guarantees the secure retrieval of original data. By contrasting with existing solutions that rely on encryption proxies, the proposed system offers enhanced security and user control over data access permissions. This research addresses the challenge of securing unstructured data within cloud storage, a prevalent mode of information exchange among diverse entities. The technique’s ability to seamlessly preserve data utility and security aligns with contemporary cyber security imperatives.