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An inference system for detecting firewall filtering rules anomalies

Identifieur interne : 004603 ( Main/Exploration ); précédent : 004602; suivant : 004604

An inference system for detecting firewall filtering rules anomalies

Auteurs : Tarek Abbes ; Adel Bouhoula [Tunisie] ; Michael Rusinowitch [France]

Source :

RBID : Hal:inria-00329730

English descriptors

Abstract

Firewalls are crucial equipments for protecting private networks. However by only deploying firewalls, administrators are far from securing their enterprises networks. Bad configurations may cause serious security breaches and network vulnerabilities. In particular, conflicting filtering rules lead to block legitimate traffic or to accept unwanted packets. We present in this paper a new classification method to detect overlaps between packet filters within one firewall. Our method processes a set of filtering rules that have a variable number of fields. A field has a range of values, represented by an interval or a variable length bit string, that may intersect with the corresponding field ranges of other rules. In order to detect overlaps we organize the conditions of each filtering rule in such a way that we can quickly separate non overlapping rules. This strategy allows us to avoid considering the entire rule header in many cases.

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Le document en format XML

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<term>inference system</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">Firewalls are crucial equipments for protecting private networks. However by only deploying firewalls, administrators are far from securing their enterprises networks. Bad configurations may cause serious security breaches and network vulnerabilities. In particular, conflicting filtering rules lead to block legitimate traffic or to accept unwanted packets. We present in this paper a new classification method to detect overlaps between packet filters within one firewall. Our method processes a set of filtering rules that have a variable number of fields. A field has a range of values, represented by an interval or a variable length bit string, that may intersect with the corresponding field ranges of other rules. In order to detect overlaps we organize the conditions of each filtering rule in such a way that we can quickly separate non overlapping rules. This strategy allows us to avoid considering the entire rule header in many cases.</div>
</front>
</TEI>
<affiliations>
<list>
<country>
<li>France</li>
<li>Tunisie</li>
</country>
<region>
<li>Franche-Comté</li>
<li>Grand Est</li>
<li>Lorraine (région)</li>
</region>
<settlement>
<li>Belfort</li>
<li>Besançon</li>
<li>Nancy</li>
</settlement>
<orgName>
<li>Institut national polytechnique de Lorraine</li>
<li>Université Nancy 2</li>
<li>Université de Bourgogne Franche-Comté</li>
<li>Université de Franche-Comté</li>
<li>Université de Lorraine</li>
<li>Université de technologie de Belfort-Montbéliard</li>
</orgName>
</list>
<tree>
<noCountry>
<name sortKey="Abbes, Tarek" sort="Abbes, Tarek" uniqKey="Abbes T" first="Tarek" last="Abbes">Tarek Abbes</name>
</noCountry>
<country name="Tunisie">
<noRegion>
<name sortKey="Bouhoula, Adel" sort="Bouhoula, Adel" uniqKey="Bouhoula A" first="Adel" last="Bouhoula">Adel Bouhoula</name>
</noRegion>
</country>
<country name="France">
<region name="Grand Est">
<name sortKey="Rusinowitch, Michael" sort="Rusinowitch, Michael" uniqKey="Rusinowitch M" first="Michael" last="Rusinowitch">Michael Rusinowitch</name>
</region>
</country>
</tree>
</affiliations>
</record>

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