| Publisher | Baghdad University | ||
|---|---|---|---|
| Format | 1.4MB PDF | Date added | 01 Feb 2009 |
| Topics | Artificial Intelligence, Network Security, Denial of Service | ||
| Downloads | 4 | ||
This paper describes novel work in using Genetic Algorithm for detecting misuse of programs. A brief overview of Intrusion Detection System, genetic algorithm and related detection techniques is presented. Developing rules manually through incorporation of attack signatures results is meaningful but weak as it is difficult to define thresholds. In this paper the proposition of learning the Intrusion Detection, rules based on genetic algorithms is presented. The experimental results are demonstrated on the KDD cup 99 and UoP intrusion detection data set (in the DARPA evaluations) in the experiments the characters of an attack such as Smurf and Apache2 (Denial of Service Attacks) are summarized through the KDD 99 data set and the effectiveness and robustness of the approach are discussed.
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