Detection of Web Defacements by means of Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  title =        "Detection of Web Defacements by means of Genetic
  author =       "Eric Medvet and Cyril Fillon and Alberto Bartoli",
  booktitle =    "Third International Symposium on Information Assurance
                 and Security, IAS 2007",
  year =         "2007",
  editor =       "Ning Zhang and Ajith Abraham",
  pages =        "227--234",
  address =      "Manchester",
  month =        "29-31 " # aug,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, Internet, Web
                 sites, computer crime, Web detection, Web pages, Web
                 site defacement, domain-specific knowledge,
                 evolutionary computation",
  DOI =          "doi:10.1109/IAS.2007.13",
  abstract =     "Web site defacement, the process of introducing
                 unauthorized modifications to a Web site, is a very
                 common form of attack. Detecting such events
                 automatically is very difficult because Web pages are
                 highly dynamic and their degree of dynamism may vary
                 widely across different pages. In this paper we propose
                 a novel detection approach based on genetic programming
                 (GP), an established evolutionary computation paradigm
                 for automatic generation of algorithms. What makes GP
                 particularly attractive in this context is that it does
                 not rely on any domain-specific knowledge, whose
                 description and synthesis is invariably a hard job. In
                 a preliminary learning phase, GP builds an algorithm
                 based on a sequence of readings of the remote page to
                 be monitored and on a sample set of attacks. Then, we
                 monitor the remote page at regular intervals and apply
                 that algorithm, which raises an alert when a suspect
                 modification is found. We developed a prototype based
                 on a broader Web detection framework we proposed
                 earlier and we tested our approach over a dataset of 15
                 dynamic Web pages, observed for about a month, and a
                 collection of real Web defacements. We compared the
                 results to those of a solution we developed earlier,
                 whose design embedded a substantial amount of domain
                 specific knowledge, and the results clearly show that
                 GP may be an effective approach for this job.",
  notes =        " Also known as \cite{4299779}",

Genetic Programming entries for Eric Medvet Cyril Fillon Alberto Bartoli