A feature selection algorithm combining information gain and multi-objective genetic search for intrusion detection system

In order to improve the detection rate and speed of intrusion detection system, this paper proposes a feature selection algorithm. The algorithm uses information gain to rank the features in descending order, and then uses a multi-objective genetic algorithm to gradually search the ranking features...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:MATEC web of conferences Ročník 336; s. 8008
Hlavní autor: Xie, Tao
Médium: Journal Article Konferenční příspěvek
Jazyk:angličtina
Vydáno: Les Ulis EDP Sciences 2021
Témata:
Algorithms
Feature selection
Genetic algorithms
Intrusion detection systems
Multiple objective analysis
ISSN:2261-236X, 2274-7214, 2261-236X
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In order to improve the detection rate and speed of intrusion detection system, this paper proposes a feature selection algorithm. The algorithm uses information gain to rank the features in descending order, and then uses a multi-objective genetic algorithm to gradually search the ranking features to find the optimal feature combination. We classified the Kddcup98 dataset into five classes, DOS, PROBE, R2L, and U2R, and conducted numerous experiments on each class. Experimental results show that for each class of attack, the proposed algorithm can not only speed up the feature selection, but also significantly improve the detection rate of the algorithm.
Bibliografie:ObjectType-Conference Proceeding-1
SourceType-Conference Papers & Proceedings-1
content type line 21
ISSN:2261-236X
2274-7214
2261-236X
DOI:10.1051/matecconf/202133608008