@article{(Open Science Index):https://publications.waset.org/pdf/1001,
	  title     = {Artificial Neural Network based Web Application Firewall for SQL Injection},
	  author    = {Asaad Moosa},
	  country	= {},
	  institution	= {},
	  abstract     = {In recent years with the rapid development of Internet and the Web, more and more web applications have been deployed in many fields and organizations such as finance, military, and government. Together with that, hackers have found more subtle ways to attack web applications. According to international statistics, SQL Injection is one of the most popular vulnerabilities of web applications. The consequences of this type of attacks are quite dangerous, such as sensitive information could be stolen or authentication systems might be by-passed. To mitigate the situation, several techniques have been adopted. In this research, a security solution is proposed using Artificial Neural Network to protect web applications against this type of attacks. The solution has been experimented on sample datasets and has given promising result. The solution has also been developed in a prototypic web application firewall called ANNbWAF.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {4},
	  number    = {4},
	  year      = {2010},
	  pages     = {610 - 619},
	  ee        = {https://publications.waset.org/pdf/1001},
	  url   	= {https://publications.waset.org/vol/40},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 40, 2010},
	}