In the age of cloud computing, the security of sensitive data is a concern for individuals and large corporations, as the amount of data stored there continues to increase. Using a confidentiality-based data categorization system, this research introduces a new way to optimize cloud storage data security. Data types, contents, and possible consequences of exposure are some of the predetermined criteria used in the proposed system to classify data into public, semi-private, and extremely sensitive categories. By utilizing encryption methods, the system automatically sorts and protects data based on its degree of secrecy. By assigning the utmost priority to protecting sensitive data and reserving less stringent safeguards for less important data, the categorization process improves the efficacy of data management. To improve cloud storage data security, the Improved Confidentiality-Based Security Algorithm (ICBSA) sorts data into different degrees of secrecy and uses individualized encryption methods. The method optimizes security and resource use by dynamically adjusting security measures depending on the categorization of the material. In addition to improving data privacy, our technology optimizes performance in cloud settings by reducing the computational cost of standard, one-size-fits-all encryption solutions. When put into place, this method has the potential to greatly reduce the dangers of data breaches, illegal access, and other security issues in cloud storage.