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Web Application Attacks Detection: A Survey and Classification

by Nadya Elbachir El Moussaid, Ahmed Toumanari
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 12
Year of Publication: 2014
Authors: Nadya Elbachir El Moussaid, Ahmed Toumanari
10.5120/18123-9085

Nadya Elbachir El Moussaid, Ahmed Toumanari . Web Application Attacks Detection: A Survey and Classification. International Journal of Computer Applications. 103, 12 ( October 2014), 1-6. DOI=10.5120/18123-9085

@article{ 10.5120/18123-9085,
author = { Nadya Elbachir El Moussaid, Ahmed Toumanari },
title = { Web Application Attacks Detection: A Survey and Classification },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 12 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number12/18123-9085/ },
doi = { 10.5120/18123-9085 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:34:21.038342+05:30
%A Nadya Elbachir El Moussaid
%A Ahmed Toumanari
%T Web Application Attacks Detection: A Survey and Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 12
%P 1-6
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The number of attacks is increasing day by day, especially the web attacks due to the shift of the majority of companies towards web applications. Therefore, the security of their sensitive data against attackers becomes a crucial matter for all organization and companies. Thus the necessity to use intrusion detection systems are required in order to increases the protection and prevent attackers from exploiting these data in illegal way. In this paper we begin by giving a survey of web application attacks and vulnerabilities, also approaches to improve the web application security using intrusion detection systems and scanners based on machine learning and artificial intelligence. When it comes to vulnerability, it is also an attack which exploits this vulnerability; therefore our paper presents web intrusion detection system based on detection of web vulnerabilities. Experimental results have been acquired from HTTP simulations in our network and from responses of HTTP requests sent to a bunch of websites and applications to test the efficiency of our intrusion detection system. This efficiency can be noticed from a High detection rate which is greater than 90%.

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Index Terms

Computer Science
Information Sciences

Keywords

Web Application Security Web Application Vulnerabilities Intrusion Detection System (IDS) Classification Machine learning Weka.

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