Enhanced Deep Learning Based Network Security Defense in Database Security Service with Big Data Analysis

Big data is growing as more public and commercial organisations collect domain-specific data. The two main data science areas are deep learning and big data analytics. This data could be used for cyber security, national intelligence, marketing, health informatics, and fraud detection. Traditional data protection systems have significant false-positive rates, low detection efficacy, and inability to handle advanced network security threats. This study suggests deep learning and big data analysis-based network security for commercial businesses. This research uses deep learning and data analysis to improve database security with a network security defensive system. Big data analysis requires data collection and processing to feed the deep neural network being built. To prove that the proposed solutions are better than current security models, they are tested. Numbers suggest deep learning and big data analysis provide the best security. The suggested method's numerical output increases risk assessment (95.4%), internet bandwidth (94.81%), accuracy (97.8%), sensitivity ratio (96.45%), and quality trade-offs between approaches (99.3%).