Prediction of SQL Injection Attacks in Web Applications

Abstract

In today’s present time, SQL injection has become a
significant security threat over the web for diverse
dynamic web applications and websites. SQL
Injection may be a sort of associate injection attack
that produces it doable to execute malicious SQL
statements into an online application consisting of
SQL information. Attackers use these SQL Injection
Queries or Statements specified if an Internet site or
an application hosted on web contain SQL
vulnerabilities to bypass application security
measures. The Attacker will even go around
authentication associated with authorization of an
online page or Internet application and might bypass
these methods and retrieve the content of the whole
SQL information of an online application. The
purpose of the proposed system is to predict the
occurrence of a SQL injection attack on a particular
server where an application is deployed from a given
supply at a particular point in time. This predictive
experiment is managed using the JMeter tool. From
network logs, you can now pre-measure, exclude
choices, analyze, and feed machine learning models
to predict SQLIA.