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inria-00546171, version 1

An Autonomic Testing Framework for IPv6 Configuration Protocols

Sheila Becker 12, Humberto Abdelnur 1, Radu State 3, Thomas Engel 2

4th International Conference on Autonomous Infrastructure, Management and Security - AIMS 2010 6155 (2010) 65-76

Abstract: 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.

  • 1:  MADYNES (INRIA Lorraine - LORIA)
  • INRIA – CNRS : UMR7503 – Université Henri Poincaré - Nancy I – Université Nancy II – Institut National Polytechnique de Lorraine (INPL)
  • 2:  Université du Luxembourg (Uni.lu)
  • Université du Luxembourg
  • 3:  Interdisciplinary Centre for Security Reliability and Trust (SnT)
  • Université du Luxembourg
  • Domain : Computer Science/Networking and Telecommunication
  • Keywords : fuzzing – IPv6 – reinforcement learning
  • Comment : The original publication is available at www.springerlink.com
 
  • inria-00546171, version 1
  • oai:hal.inria.fr:inria-00546171
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  • Submitted on: Tuesday, 14 December 2010 10:55:00
  • Updated on: Thursday, 16 December 2010 11:41:29