@inproceedings{9e9a3d40acb247668779f4181606347e,
title = "Detection of non-content based attacks using GA with extended KDD features",
abstract = "Detection attack tools have a very wide range of solutions, from the applications of rules obtained by experience to the use of machine learning techniques, including multiple bioinspired methods. In order to analyze the results of research methods for attack detection, the DARPA KDD data set have been widely used but their data are outdated for various kinds of attacks. A software called Spleen designed to get data from a tested network with the same structure of DARPA data set is introduced. The application is used to complete the data set with additional features according to an attack analysis. In order to show advantages of an extended data set, two genetic methods in the detection of non-content based attacks are tested.",
keywords = "Adaptative algorithm, Genetic algorithms, Information security, Intrusion detection, KDD, Machine learning TCPIP",
author = "Edward Guill{\'e}n and Jhordany Rodriguez and Rafael P{\'a}ez and Andrea Rodriguez",
note = "Publisher Copyright: {\textcopyright} 2012 Newswood Limited. All rights reserved.; 2012 World Congress on Engineering and Computer Science, WCECS 2012 ; Conference date: 24-10-2012 Through 26-10-2012",
year = "2012",
language = "English",
isbn = "9789881925114",
series = "Lecture Notes in Engineering and Computer Science",
publisher = "Newswood Limited",
pages = "30--35",
editor = "Jon Burgstone and Ao, {S. I.} and Craig Douglas and Grundfest, {W. S.}",
booktitle = "International MultiConference of Engineers and Computer Scientists, IMECS 2012",
}