sql injection kdd dataset
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In the real world, dependence on the applications of the World Wide Web increased day by day and became vulnerable to security attacks. Of all the different attacks, SQL injection attacks are the most common. In this article we propose the prevention of SQL injection vulnerability through the decision tree classification technique. The proposed model uses the famous decision tree classification model to avoid SQL injection attacks. The proposed model will filter the HTTP request sent using a decision tree classification attack signature.


SQL Injection (SQLi) refers to an injection attack in which an attacker can execute malicious SQL statements that also control the database server of a web application (also known as a Relational Database Management System - RDBMS ). Because an SQL Injection vulnerability could affect any Web site or Web application that uses an SQL-based database, the vulnerability is one of the oldest, most frequent, and most dangerous Web application vulnerabilities.

Taking advantage of a SQL Injection vulnerability, given the right circumstances, an attacker can use it to avoid mechanisms for authentication and authorization of a web application and retrieve the contents of a complete database. SQL Injection can also be used to add, modify and delete records in a database, affecting the integrity of the data.

SQL Injection can provide an attacker with unauthorized access to sensitive data including customer data, personally identifiable information (PII), trade secrets, intellectual property and other sensitive information.
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