InforLorV4, Hal, Corpus, bibRecord, 000A96

Activity Monitoring for large honeynets and network telescopes

Identifieur interne : 000A96 ( Hal/Corpus ); précédent : 000A95; suivant : 000A97

Activity Monitoring for large honeynets and network telescopes

Auteurs : Jérôme François ; Radu State ; Olivier Festor

Source :

International Journal On Advances in Systems and Measurements [ 1942-261X ] ; 2008.

RBID : Hal:inria-00392566

English descriptors

mix :
- backscatter, centrality, honeypot, intersection graphs, locality statistics, monitoring, telescope.

Abstract

This paper proposes a new distributed monitoring approach based on the notion of centrality of a graph and its evolution in time. We consider an activity profiling method for a distributed monitoring platform and illustrate its usage in two different target deployments. The first one concerns the monitoring of a distributed honeynet, while the second deployment target is the monitoring of a large network telescope. The central concept underlying our work are the intersection graphs and a centrality based locality statistics. These graphs have not been used widely in the field of network security. The advantage of this method is that analyzing aggregated activity data is possible by considering the curve of the maximum locality statistics and that important change point moments are well identified.

Url:

https://hal.inria.fr/inria-00392566

Links to Exploration step

Hal:inria-00392566

Le document en format XML

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<front><div type="abstract" xml:lang="en">This paper proposes a new distributed monitoring approach based on the notion of centrality of a graph and its evolution in time. We consider an activity profiling method for a distributed monitoring platform and illustrate its usage in two different target deployments. The first one concerns the monitoring of a distributed honeynet, while the second deployment target is the monitoring of a large network telescope. The central concept underlying our work are the intersection graphs and a centrality based locality statistics. These graphs have not been used widely in the field of network security. The advantage of this method is that analyzing aggregated activity data is possible by considering the curve of the maximum locality statistics and that important change point moments are well identified.</div>
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<abstract xml:lang="en">This paper proposes a new distributed monitoring approach based on the notion of centrality of a graph and its evolution in time. We consider an activity profiling method for a distributed monitoring platform and illustrate its usage in two different target deployments. The first one concerns the monitoring of a distributed honeynet, while the second deployment target is the monitoring of a large network telescope. The central concept underlying our work are the intersection graphs and a centrality based locality statistics. These graphs have not been used widely in the field of network security. The advantage of this method is that analyzing aggregated activity data is possible by considering the curve of the maximum locality statistics and that important change point moments are well identified.</abstract>
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Activity Monitoring for large honeynets and network telescopes

Activity Monitoring for large honeynets and network telescopes

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