An Autonomic Testing Framework for IPv6 Configuration Protocols

Sheila Becker (1, 2) , Humberto Abdelnur (1) , Radu State (3) , Thomas Engel (2)

1 MADYNES - Management of dynamic networks and services
2 Uni.lu - Université du Luxembourg
3 SnT - Interdisciplinary Centre for Security, Reliability and Trust [Luxembourg]

The current underutilization of IPv6 enabled services makes accesses to them very attractive because of higher availability and better response time, like the IPv6 specific services from Google and Youtube have recently got a lot of requests. In this paper, we describe a fuzzing framework for IPv6 protocols. Fuzzing is a process by which faults are injected in order to find vulnerabilities in implementations. Our paper describes a machine learning approach, that leverages reinforcement based fuzzing method. We describe a reinforcement learning algorithm to allow the framework to autonomically learn the best fuzzing mechanisms and to automatically test stability and reliability of IPv6.

Mots clés: fuzzing; IPv6; reinforcement learning

Domaines: Réseaux et télécommunications [cs.NI]

Sheila Becker, Humberto Abdelnur, Radu State, Thomas Engel. An Autonomic Testing Framework for IPv6 Configuration Protocols. 4th International Conference on Autonomous Infrastructure, Management and Security - AIMS 2010, University of Zurich, Jun 2010, Zurich, Switzerland. pp.65-76, ⟨10.1007/978-3-642-13986-4_7⟩. ⟨inria-00546171⟩