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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD)
An International Open Access Journal |   ISSN: 2456-4184 |  IMPACT FACTOR: 5.57

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Paper Title: AN INTRUSION DETECTION SYSTEM FOR SQL INJECTION ATTACK USING MACHINE LEARNING METHOD
Authors Name: PRIYANKA YADAV , DR ABHA CHOUBEY
Author Reg. ID:
IJNRD_170136
Published Paper Id: IJNRD1709006
Published In: Volume 2 Issue 9, September-2017
Abstract: Most of the administrations in the world uses the web as a medium for their day to day communications and businesses transactions. The strength of all web based applications are Relational Data base which are functioned by Structured Query Language (SQL). As the web becomes more prevalent, web attacks are increasing day by day. SQL Injection Attacks (SQLIAs)-Structured Query Language (SQL) is an interpreted language used in database driven web applications which construct SQL statements that incorporate user-supplied data or text. , if this happened in an precarious manner, then the web application may be susceptible to SQL Injection Attack i.e. If user abounding data is not appropriately authenticated then user can amend or expertise a malevolent SQL statements and can execute haphazard code on the machine or can alter the contents of database. In this paper we will use machine learning algorithm (classification) for detection of SQL injection over web application also measured the performance of proposed SQL injection classifier output with SVM classifier.
Keywords: IDS;SQL,XSS;SQL;ML
Cite Article: "AN INTRUSION DETECTION SYSTEM FOR SQL INJECTION ATTACK USING MACHINE LEARNING METHOD", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.2, Issue 9, page no.17-21, September-2017, Available :http://www.ijnrd.org/papers/IJNRD1709006.pdf
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