A closer look at Intrusion Detection System for web applications

Intrusion Detection System (IDS) is one of the security measures being used as an additional defence mechanism to prevent the security breaches on web. It has been well known methodology for detecting network-based attacks but still immature in the domain of securing web application. The objective of the paper is to thoroughly understand the design methodology of the detection system in respect to web applications. In this paper, we discuss several specific aspects of a web application in detail that makes challenging for a developer to build an efficient web IDS. The paper also provides a comprehensive overview of the existing detection systems exclusively designed to observe web traffic. Furthermore, we identify various dimensions for comparing the IDS from different perspectives based on their design and functionalities. We also provide a conceptual framework of an IDS with prevention mechanism to offer a systematic guidance for the implementation of the system specific to the web applications. We compare its features with five existing detection systems, namely AppSensor, PHPIDS, ModSecurity, Shadow Daemon and AQTRONIX WebKnight. The paper will highly facilitate the interest groups with the cutting edge information to understand the stronger and weaker sections of the web IDS and provide a firm foundation for developing an intelligent and efficient system

A Framework for Hybrid Intrusion Detection Systems

Web application security is a definite threat to the world’s information technology infrastructure. The Open Web Application Security Project (OWASP), generally defines web application security violations as unauthorized or unintentional exposure, disclosure, or loss of personal information. These breaches occur without the company’s knowledge and it often takes a while before the web application attack is revealed to the public, specifically because the security violations are fixed. Due to the need to protect their reputation, organizations have begun researching solutions to these problems. The most widely accepted solution is the use of an Intrusion Detection System (IDS). Such systems currently rely on either signatures of the attack used for the data breach or changes in the behavior patterns of the system to identify an intruder. These systems, either signature-based or anomaly-based, are readily understood by attackers. Issues arise when attacks are not noticed by an existing IDS because the attack does not fit the pre-defined attack signatures the IDS is implemented to discover. Despite current IDSs capabilities, little research has identified a method to detect all potential attacks on a system. This thesis intends to address this problem. A particular emphasis will be placed on detecting advanced attacks, such as those that take place at the application layer. These types of attacks are able to bypass existing IDSs, increase the potential for a web application security breach to occur and not be detected. In particular, the attacks under study are all web application layer attacks. Those included in this thesis are SQL injection, cross-site scripting, directory traversal and remote file inclusion. This work identifies common and existing data breach detection methods as well as the necessary improvements for IDS models. Ultimately, the proposed approach combines an anomaly detection technique measured by cross entropy and a signature-based attack detection framework utilizing genetic algorithm. The proposed hybrid model for data breach detection benefits organizations by increasing security measures and allowing attacks to be identified in less time and more efficiently

Analyse de vulnérabilités et évaluation de systèmes de détection d'intrusions pour les applications Web.

Avec le développement croissant d Internet, les applications Web sont devenues de plus en plus vulnérables et exposées à des attaques malveillantes pouvant porter atteinte à des propriétés essentielles telles que la confidentialité, l intégrité ou la disponibilité des systèmes d information. Pour faire face à ces malveillances, il est nécessaire de développer des mécanismes de protection et de test (pare-feu, système de détection d intrusion, scanner Web, etc.) qui soient efficaces. La question qui se pose est comment évaluer l efficacité de tels mécanismes et quels moyens peut-on mettre en oeuvre pour analyser leur capacité à détecter correctement des attaques contre les applications web.Dans cette thèse nous proposons une nouvelle méthode, basée sur des techniques de clustering de pages Web, qui permet d identifier les vulnérabilités à partir de l analyse selon une approche boîte noire de l application cible. Chaque vulnérabilité identifiée est réellement exploitée ce qui permet de s assurer que la vulnérabilité identifiée ne correspond pas à un faux positif. L approche proposée permet également de mettre en évidence différents scénarios d attaque potentiels incluant l exploitation de plusieurs vulnérabilités successives en tenant compte explicitement des dépendances entre les vulnérabilités.Nous nous sommes intéressés plus particulièrement aux vulnérabilités de type injection de code, par exemple les injections SQL. Cette méthode s est concrétisée par la mise en oeuvre d un nouveau scanner de vulnérabilités et a été validée expérimentalement sur plusieurs exemples d applications vulnérables. Nous avons aussi développé une plateforme expérimentale intégrant le nouveau scanner de vulnérabilités, qui est destinée à évaluer l efficacité de systèmes de détection d intrusions pour des applications Web dans un contexte qui soit représentatif des menaces auxquelles ces applications seront confrontées en opération. Cette plateforme intègre plusieurs outils qui ont été conçus pour automatiser le plus possible les campagnes d évaluation. Cette plateforme a été utilisée en particulier pour évaluer deux techniques de détection d intrusions développées par nos partenaires dans le cadre d un projet de coopération financé par l ANR, le projet DALI.With the increasing development of Internet, Web applications have become increasingly vulnerable and exposed to malicious attacks that could affect essential properties such as confidentiality, integrity or availability of information systems. To cope with these threats, it is necessary to develop efficient security protection mechanisms and testing techniques (firewall, intrusion detection system,Web scanner, etc..). The question that arises is how to evaluate the effectiveness of such mechanisms and what means can be implemented to analyze their ability to correctly detect attacks against Webapplications.This thesis presents a new methodology, based on web pages clustering, that is aimed at identifying the vulnerabilities of a Web application following a black box analysis of the target application. Each identified vulnerability is actually exploited to ensure that the identified vulnerability does not correspond to a false positive. The proposed approach can also highlight different potential attack scenarios including the exploitation of several successive vulnerabilities, taking into account explicitly the dependencies between these vulnerabilities. We have focused in particular on code injection vulnerabilities, such asSQL injections. The proposed method led to the development of a new Web vulnerability scanner and has been validated experimentally based on various vulnerable applications.We have also developed an experimental platform integrating the new web vulnerability scanner, that is aimed at assessing the effectiveness of Web applications intrusion detection systems, in a context that is representative of the threats that such applications face in operation. This platform integrates several tools that are designed to automate as much as possible the evaluation campaigns. It has been used in particular to evaluate the effectiveness of two intrusion detection techniques that have been developed by our partners of the collaborative project DALI, funded by the ANR, the French National Research AgencyTOULOUSE-INSA-Bib. electronique (315559905) / SudocSudocFranceF

Detecting Attacks Against Data in Web Applications

International audienc

An Invariant-based Approach for Detecting Attacks against Data in Web Applications

International audienceRRABIDS (Ruby on Rails Anomaly Based Intrusion Detection System) is an application levelintrusion detection system (IDS) for applications implemented with the Ruby on Railsframework. The goal of this intrusion detection system is to detect attacks against data in thecontext of web applications. This anomaly based IDS focuses on the modelling of the normalapplication profile using invariants. These invariants are discovered during a learning phase.Then, they are used to instrument the web application at source code level, so that a deviationfrom the normal profile can be detected at run-time. This paper illustrates on simple exampleshow the approach detects well-known categories of web attacks that involve a state violation ofthe application, such as SQL injections. Finally, an assessment phase is performed to evaluatethe accuracy of the detection provided by the proposed approach