Research On Online Intelligent Detection Technology Of SQL Injection Behavior

With the rapid development of information technology represented by the Internet,various Internet applications such as network media and business platforms have developed rapidly.At the same time,malicious behaviors on the Internet have shown rapid growth in recent years.SQL injection behavior is a common type of hidden network security risk.Early awareness of this type of behavior is of great value for catching malicious users hidden behind it and eliminating security risks in time.At present,the online detection of SQL injection behavior has the problem of low acc.In recent years,artificial intelligence technology has developed vigorously,especially the wide application of deep learning technology,which provides a reference for solving this problem.In order to effectively apply the advantages of deep learning technology to SQL injection behavior online detection,this paper proposes a script data preprocessing and conversion method that focuses on key features,which can effectively highlight the characteristics of SQL injection behavior script data and improve real-time online operation detection Time efficiency;Constructed a SQL injection behavior data detection neural network model based on deep learning technology,and improved the feature extraction ability of SQL script data by introducing fast Fourier transform.Experiments were conducted on SQL injection behavior data sets.The results show that the model can effectively improve detection.Designed and implemented a prototype system for SQL injection behavior online detection oriented to data packet load and characteristics,and verified the feasibility and effectiveness of the above results online.In this paper,the online detection of SQL injection behavior is an active attempt and exploration of the identification and detection of malicious behaviors on the network,and provides ideas and methods for other network script data analysis and processing.