Towards Effective Network Intrusion Detection: A Hybrid Model Integrating Gini Index and GBDT with PSO
Joint Authors
Cheng, Jianjun
Bai, Shenshen
Yu, Yang
Chen, Xiaoyun
Li, Longjie
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-26
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
In order to protect computing systems from malicious attacks, network intrusion detection systems have become an important part in the security infrastructure.
Recently, hybrid models that integrating several machine learning techniques have captured more attention of researchers.
In this paper, a novel hybrid model was proposed with the purpose of detecting network intrusion effectively.
In the proposed model, Gini index is used to select the optimal subset of features, the gradient boosted decision tree (GBDT) algorithm is adopted to detect network attacks, and the particle swarm optimization (PSO) algorithm is utilized to optimize the parameters of GBDT.
The performance of the proposed model is experimentally evaluated in terms of accuracy, detection rate, precision, F1-score, and false alarm rate using the NSL-KDD dataset.
Experimental results show that the proposed model is superior to the compared methods.
American Psychological Association (APA)
Li, Longjie& Yu, Yang& Bai, Shenshen& Cheng, Jianjun& Chen, Xiaoyun. 2018. Towards Effective Network Intrusion Detection: A Hybrid Model Integrating Gini Index and GBDT with PSO. Journal of Sensors،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1200737
Modern Language Association (MLA)
Li, Longjie…[et al.]. Towards Effective Network Intrusion Detection: A Hybrid Model Integrating Gini Index and GBDT with PSO. Journal of Sensors No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1200737
American Medical Association (AMA)
Li, Longjie& Yu, Yang& Bai, Shenshen& Cheng, Jianjun& Chen, Xiaoyun. Towards Effective Network Intrusion Detection: A Hybrid Model Integrating Gini Index and GBDT with PSO. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1200737
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1200737