DocumentCode :
3580259
Title :
Improving Web Application Firewalls to detect advanced SQL injection attacks
Author :
Makiou, Abdelhamid ; Begriche, Youcef ; Serhrouchni, Ahmed
Author_Institution :
Telecom ParisTech, Paris, France
fYear :
2014
Firstpage :
35
Lastpage :
40
Abstract :
Injections flaws which include SQL injection are the most prevalent security threats affecting Web applications[1]. To mitigate these attacks, Web Application Firewalls (WAFs) apply security rules in order to both inspect HTTP data streams and detect malicious HTTP transactions. Nevertheless, attackers can bypass WAF´s rules by using sophisticated SQL injection techniques. In this paper, we introduce a novel approach to dissect the HTTP traffic and inspect complex SQL injection attacks. Our model is a hybrid Injection Prevention System (HIPS) which uses both a machine learning classifier and a pattern matching inspection engine based on reduced sets of security rules. Our Web Application Firewall architecture aims to optimize detection performances by using a prediction module that excludes legitimate requests from the inspection process.
Keywords :
Internet; SQL; firewalls; learning (artificial intelligence); pattern classification; pattern matching; telecommunication traffic; transport protocols; HIPS; HTTP data streams; WAF rules; Web application firewall architecture; complex SQL injection attack detection; hybrid injection prevention system; legitimate requests; machine learning classifier; malicious HTTP transaction detection; pattern matching inspection engine; prediction module; reduced sets; security rules; security threats; Servers; HTTP dissection; SQL injection; Security rules; Web Application Firewall; machine learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Assurance and Security (IAS), 2014 10th International Conference on
Print_ISBN :
978-1-4799-8098-7
Type :
conf
DOI :
10.1109/ISIAS.2014.7064617
Filename :
7064617
Link To Document :
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