Data sharing is made easy by cloud computing, but data security is a major problem because of online threats. For patient privacy and to guarantee data security, protecting medical data on the cloud is essential. A potential cryptographic method called homomorphic encryption enables computations to be conducted on encrypted information without the need for the decryption maintaining privacy of information. In this study, we propose an efficient optimized spider monkey-based Paillier homomorphic cryptosystem model, referred to as SP-PHC, for cloud-based data security of medical records. We gather medical datasets from the data repository and incorporate them into the envisioned SP-PHC scheme to protect against unauthorized access by third-party attackers. Sensitive medical data are encrypted using the Paillier homomorphic encryption (PHE) technique to maintain privacy. Our model not only strengthens the security of sensitive health data but also makes it easier to analyze the information in a way that preserves privacy in the cloud. Empirical findings underline the strength of our solution in terms of encryption and decryption, reaffirming its validity in protecting medical data in the cloud.