System Security Using Artificial Intelligence and Reduction of Data Breach
M. Avrit, G. P. Siranjeevi, Shruti Mishra, Sandeep Kumar Satapathy, Priyanka Mishra, Pradeep Kumar Mallick, Gyoo Soo Chae · 2025
This presentation focuses on the integration of artificial intelligence (AI) with cloud security to address growing concerns about data breaches and strengthen security intelligence and audit processes. The problem statement highlights the difficulty of detecting malware files targeting sensitive data and cloud systems, as well as the significant impact of human error on data loss. The goal is to develop a defensive AI system that can adapt by self-learning using deep learning techniques for malware classification, intrusion detection, and mine intelligence detection. The motivation is the possibilities of AI technology to improve cybersecurity and minimize the vulnerabilities of cloud technology. The advantages include less data loss, improved security levels through deep learning and machine learning, malware detection and removal, and less human error. However, the downside is the need for advanced AI models, accurate data entry, third-party audits, AI security, and infrastructure requirements. The implementation plan includes two AI-powered servers, deep learning integration, and reverse tracking of corrupted data through censorship. The results of this presentation aim to strengthen cloud security, protect sensitive data, and prevent and mitigate data breaches.