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Web application has various input functions which are susceptible to SQL-Injection attack. SQL-Injection occurs by injecting suspicious code or data fragments in a web application. Personal information disclosure, loss of authenticity, data theft and site fishing falls under this attack category. It is impossible to check original data code and suspicious data code using available algorithms and approaches because of inefficient and proper training techniques of dataset or design aspects. In this paper, the authors will use SVM (Support Vector Machine) for classification and prediction of SQL-Injection attack. In their propose algorithm, SQL-Injection attack detection accuracy is (96.47% and which is the highest among the existing SQL-Injection detection Techniques.
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