An Intelligent AI-Enabled Cloud Security System for Certifying Information in Financial Sectors

Certifying information entails ensuring the correctness and validity of data. This procedure ensures that the information given is accurate and satisfies the requirements. Certification is performed by authorised persons, establishing confidence in the integrity of the information and increasing reliability for a variety of objectives. In this research, research aim is to develop an intelligent AI-enabled cloud security system for certifying information in the financial sector. This study's main focus is server-side data and compute security, which addresses the requirement for secure cloud data storage as well as additional safety precautions. Intelligent Seagull optimized ensemble Naive Bayes (ISO-ENB) has been utilised to choose the best appropriate available server for a particular job. Generally, homomorphic encryption is employed to ensure the integrity of the data that is communicated by encrypting the data before sending it to the server. The proposed model incorporates hill climbing refined Advanced Encryption Standard (HC-AES) with ISO-ENB to evaluate which server will be most profitable. Research evaluated the suggested model with various parameters such as data privacy ratio (91%), risk reduction ratio (99.1%) and scalability ratio (98%). The experimental outcomes illustrate the effectiveness of the recommended data security model. This system does provide secure mechanisms for sharing keys and backing up data, both of which are important in maintaining the privacy of sensitive data stored in the financial cloud infrastructure.