Data management has been revolutionized because cloud computing technologies have increased user barriers to expensive infrastructure and storage limits. The advantages of the cloud have made it possible for significant cloud implementation in major businesses. However, the privacy of cloud-based data remains the significant and most crucial problem for data owners due to various security risks. Many researchers have proposed various methods to maintain the confidentiality of the data, including attribute-based encryption (ABE). Though, the cloud is still dogged mainly by the security issue. To protect data privacy, the new encryption model "Advanced Encryption Standard- Improved Quantum Ciphertext Policy and Attribute-based Encryption" (AES-IQCP-ABE) is introduced in the present research. The suggested method twice encrypts the data and the attributes using the ABE at first. Second, using the AES technique, the encrypted data is encrypted before being delivered to authorized users. The dynamic, chaotic map function is used in the proposed approach to protecting user attributes throughout the initialization of the key, encryption of data, and decryption of data processes. For the encryption process, the inputs used in the proposed research are both unstructured and structured extensive medical data. Regarding computational memory, time for cloud data encryption, and decryption, the proposed model outperforms the previous ABE-based encryption and decryption algorithms.