The increasing volume of medical health data has created a need for security solutions that can identify and fix errors, as well as prevent abuses of current encryption methods, especially in key generation and access provisioning on an as-needed basis. Using the three-dimensional version of dynamic key optimization, this research advances a new framework: the Advanced Encryption Standard (3D-AES) block cipher, and the Hybrid Slime Mould Reptile Search Algorithm (HSMRSA), which is used to bind the two. The HSMRSA framework further strengthens the efficiency of the search process and has been refined to operate in conjunction with the complementary method. When integrated, the two approaches enable the generation of secure keys through established cryptographic procedures. The 3D-AES cipher, like the original AES, is extended through a three-dimensional transformation model and spatial permutation, thereby improving diffusion and overall data security. A Self-Destructive Data Object (SDO) is used for access control, and a distributed hash table (DHT) is applied to split cipher text to provide a realistic time-based security model. To ensure confidentiality, integrity, and authentication of health data, we propose an enhanced architecture.

In ensuring the security of the health data processing, this paper suggests a combination of the cloud approach. It directly tackles some of the key flaws of the prevailing system which include ineffective key generation, ineffective dynamic governance and disconnected security system. This solution represents a centralized architecture that has numerous central features. The Hybrid Slime Mould Reptile Search Algorithm (HSMRSA) will be constructed and implemented in such a way that efficient extraction of strong cryptographic keys is achieved. The other breakthrough will be a new and improved 3D-AES block cipher by adding a new three-dimensional data structure and a new spatial permutation to facilitate the most difficult confusion and diffusion of structured data, such as medical records. They will then be enhanced with a Distributed Hash Table (DHT) based storage model and Self-Destructing Data Objects to come up with a data governance model that is resilient and time-sensitive. These elements together provide us with a complete security solution and can be able to match the finest quality of secrecy of medical infrastructure with the sensitive workload demands of health care.

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