Evolving Attackers against Wireless Sensor Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Mrugala:2016:GECCOcomp,
  author =       "Kinga Mrugala and Nilufer Tuptuk and Stephen Hailes",
  title =        "Evolving Attackers against Wireless Sensor Networks",
  booktitle =    "GECCO '16 Companion: Proceedings of the Companion
                 Publication of the 2016 Annual Conference on Genetic
                 and Evolutionary Computation",
  year =         "2016",
  editor =       "Tobias Friedrich and Frank Neumann and 
                 Andrew M. Sutton and Martin Middendorf and Xiaodong Li and 
                 Emma Hart and Mengjie Zhang and Youhei Akimoto and 
                 Peter A. N. Bosman and Terry Soule and Risto Miikkulainen and 
                 Daniele Loiacono and Julian Togelius and 
                 Manuel Lopez-Ibanez and Holger Hoos and Julia Handl and 
                 Faustino Gomez and Carlos M. Fonseca and 
                 Heike Trautmann and Alberto Moraglio and William F. Punch and 
                 Krzysztof Krawiec and Zdenek Vasicek and 
                 Thomas Jansen and Jim Smith and Simone Ludwig and JJ Merelo and 
                 Boris Naujoks and Enrique Alba and Gabriela Ochoa and 
                 Simon Poulding and Dirk Sudholt and Timo Koetzing",
  pages =        "107--108",
  month =        "20-24 " # jul,
  organisation = "SIGEVO",
  address =      "Denver, USA",
  publisher =    "ACM",
  keywords =     "genetic algorithms, genetic programming: Poster",
  publisher_address = "New York, NY, USA",
  isbn13 =       "978-1-4503-4323-7",
  DOI =          "doi:10.1145/2908961.2908974",
  abstract =     "Recent technological improvements in wireless
                 communication and electronics have enabled the
                 development of small, low-cost wireless sensor nodes,
                 capable of monitoring everything from human health to
                 the performance of the electricity grid. A natural
                 consequence is a desire to secure systems containing
                 these nodes. Unfortunately, proving that systems are
                 secure is beyond the current state of the art, and
                 testing for security is problematic: test cases often
                 miss attacks that have never previously been seen. In
                 this paper, we use Genetic Programming (GP) to create
                 attacks against Internet of Things devices, to help
                 identify vulnerabilities before systems are attacked
                 for real. To assess the effectiveness of each attacker,
                 we used it against a wireless sensor network (WSN) with
                 publish-subscribe communications, protected by a
                 literature artificial immune intrusion detection system
                 (IDS). The GP attackers succeeded in suppressing
                 significantly more legitimate messages than a
                 hand-coded attacker, whilst decreasing the likelihood
                 of detection. As a consequence, it was possible to tune
                 the IDS, improving its performance. Whilst these
                 results are preliminary, they demonstrate GP holds
                 significant potential for improving the protection of
                 systems with large attack spaces.",
  notes =        "Distributed at GECCO-2016.",
}

Genetic Programming entries for Kinga Mrugala Nilufer Tuptuk Stephen Hailes

Citations