• Dr.Vineetha K R
• Jeena Thomas

Online application assaults are becoming increasingly common and severe. The large amount of data accessible on the internet motivates hackers to initiate novel attacks. Extensive study on web application security has been done in this area. Structured Query Language Injection is the most hazardous online application exploit (SQLI). This attack poses a significant risk to online apps. Several studies have been carried out in order to reduce this assault, either by avoiding it at an early stage or spotting it when it happens. We give an overview of the SQL injection attack as well as a classification of the freshly suggested detection and prevention methods in this article. This paper discusses the methodology and analysis of using machine learning techniques for SQL injection attack detection and prevention. The report covers techniques such as feature selection, model training, and evaluation, and presents various evaluation metrics such as true positive rate, false positive rate, accuracy, precision, recall, F1 score, training, and testing time. The report also emphasizes the importance of using machine learning techniques in combination with other techniques to maximize the effectiveness of the overall strategy. Additionally, the report highlights the need to regularly update and test the machine learning techniques for SQL injection attack detection and prevention represents a promising approach to improving the security of web applications that use SQL databases. The development and use of effective machine learning techniques will become increasingly important for protecting against SQL injection attacks in the future.

Keywords: SQL injection, Cyber security, Machine learning, Feature selection, Precision, Recall

" OUTBREAK DETECTION AND PREVENTION TECHNIQUE OF SQL INJECTION ATTACKING USING MACHINE LEARNING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.b292-b298, March-2023, Available :http://www.jetir.org/papers/JETIR2303137.pdf

" OUTBREAK DETECTION AND PREVENTION TECHNIQUE OF SQL INJECTION ATTACKING USING MACHINE LEARNING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppb292-b298, March-2023, Available at : http://www.jetir.org/papers/JETIR2303137.pdf