Network intrusion detection using danger theory and genetic algorithms

2Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

Abstract

One of the most concerning problems faced by practitioners, within the development and operation of IT communication networks, is the crescent number of network intrusion attempts. That kind of attacks compromise the integrity of several services provided through the Internet. This paper presents a technique capable of optimize Danger Theory-based Intrusion Detection Systems through the use of a Genetic Algorithms. To validate the approach, tests were performed on the KDD Cup 1999 database, provided by the University of California Irvine (UCI).

Cite

CITATION STYLE

APA

Lima Santanelli, J., & de Lima Neto, F. B. (2017). Network intrusion detection using danger theory and genetic algorithms. In Advances in Intelligent Systems and Computing (Vol. 557, pp. 394–405). Springer Verlag. https://doi.org/10.1007/978-3-319-53480-0_39

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free