Adaptabilty of a GP Based IDS on Wireless Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Makanju:2008:ARES,
  author =       "Adetokunbo Makanju and A. Nur Zincir-Heywood and 
                 Evangelos E. Milios",
  title =        "Adaptabilty of a GP Based IDS on Wireless Networks",
  booktitle =    "Third International Conference on Availability,
                 Reliability and Security, ARES 08",
  year =         "2008",
  month =        mar,
  pages =        "310--318",
  keywords =     "genetic algorithms, genetic programming, GP based IDS,
                 Kismet, Snort-Wireless, WiFi networks, data link layer,
                 intrusion detection system, machine learning, wireless
                 networks, learning (artificial intelligence), security
                 of data, wireless LAN",
  DOI =          "doi:10.1109/ARES.2008.50",
  abstract =     "Security and Intrusion detection in WiFi networks is
                 currently an active area of research where WiFi
                 specific Data Link layer attacks are an area of focus;
                 particularly recent work has focused on producing
                 machine learning based IDSs for these WiFi specific
                 attacks. These proposed machine learning based IDSs
                 come in addition to the already deployed signatures
                 which are already in use in conventional intrusion
                 detection systems like Snort-Wireless and Kismet. In
                 this paper, we compare the detection capability of
                 Snort-Wireless and a Genetic Programming (GP) based
                 intrusion detector, based on the ability to adapt to
                 modified attacks, ability to adapt to similar unknown
                 attacks and infrastructure independent detection. Our
                 results show that the GP based detection system is much
                 more robust against modified attacks compared to
                 Snort-Wireless. Moreover, by focusing on the method(s)
                 used in feature preprocessing for presentation to
                 learning algorithms, GP based IDSs can achieve
                 infrastructure independent detection and can adapt to
                 similar unknown attacks too. On the other hand, even
                 though Snort-Wireless is an infrastructure independent
                 detector, it cannot adapt to unknown attacks even if
                 they are similar to others for which it has signatures
                 on.",
  notes =        "Also known as \cite{4529352}",
}

Genetic Programming entries for Tokunbo Makanju Nur Zincir-Heywood Evangelos E Milios

Citations