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Title: Tunneling Activities Detection Using Machine Learning Techniques, Journal of Telecommunications and Information Technology, 2011, nr 1

Creator:

Dubois, Renaud ; Morel, Mathieu ; Allard, Fabien ; Gompel, Paul

Date:

2011, nr 1

Resource Type:

artykuł

Description:

Tunnel establishment, like HTTPS tunnel or related ones, between a computer protected by a security gateway and a remote server located outside the protected network is the most effective way to bypass the network security policy. Indeed, a permitted protocol can be used to embed a forbidden one until the remote server. Therefore, if the resulting information flow is ciphered, security standard tools such as application level gateways (ALG), firewalls, intrusion detection system (IDS), do not detect this violation. In this paper, we describe a statistical analysis of ciphered flows that allows detection of the carried inner protocol. Regarding the deployed security policy, this technology could be added in security tools to detect forbidden protocols usages. In the defence domain, this technology could help preventing information leaks through side channels. At the end of this article, we present a tunnel detection tool architecture and the results obtained with our approach on a public database containing real data flows.

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy, Warszawa

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:1159

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

network security cyberdefense hidden Markov models RandomForest decision trees HTTPS tunnel

Object collections:

Last modified:

Jan 17, 2013

In our library since:

Jan 17, 2013

Number of object content hits:

194

All available object's versions:

https://bc.itl.waw.pl/publication/1419

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Edition name Date
Allard, Fabien, 2011, nr 1, Tunneling Activities Detection Using Machine Learning Techniques, Journal of Telecommunications and Information Technology, 2011, nr 1 Jan 17, 2013

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Address

Instytut Łączności – Państwowy Instytut Badawczy ul. Szachowa 1 04-894 Warszawa

Phone

(+48) 5128 696

E-Mail

biblioteka@il-pib.pl

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