A Sample Proposal Enhancing the Security of the Cloud Computing System Through Deep Learning and Data Mining

Abstract

Malware or malicious applications can cause catastrophic damage to not only computer systems but also data centers, web, and mobile applications from various industries; the Ministry of Interior, in particular, is the most important educational institution because they are more vulnerable to security breaches. Keeping stakeholder data safe from unwanted actors is a big concern that brings us to the concept of malware detection and prevention. Deep learning and data mining using artificial intelligence (AI) can be an efficient approach for developing anti-malware systems. Following suit, this study gave a thorough examination of malware detection methodologies and procedures. Initially, we attempted to provide a comprehensive description of malware, artificial intelligence, and data mining, as well as a listing of these technologies. The suggested system was described (whether this data is files, photographs, videos, or import limitations and is processed and identified by mining and deep learning data, and the system was trained on data). So far, our findings suggest that artificial intelligence and data mining can be used to construct anti-malware systems to detect and prevent malware assaults or security threats in software applications geared toward technological wonderland and its real-world application in the Ministry of Interior. To conclude, we outline dozens of possibilities for overcoming the observed restrictions and intend to expressly continue our efforts toward significant advancements in malware detection and prevention by implementing this proposal. We give a detailed look at the current ways to find malware, their flaws, and ways to make them more effective. We also explain how we're working on integrating the system. Our study shows that adopting future approaches to developing malware detection applications should provide significant advantages. Understanding this structure should help researchers do more research on malware detection and prevention using AI and data mining.