Research Repository

A Collaborative Intrusion Detection Model Using a Novel Optimal Weight Strategy Based on Genetic Algorithm for Ensemble Classifier

Tengl, S, Zhang, Z, Teng, Luyao, Zhang, W, Zhu, H, Fang, X and Fei, L (2018) A Collaborative Intrusion Detection Model Using a Novel Optimal Weight Strategy Based on Genetic Algorithm for Ensemble Classifier. In: 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design (CSCWD), 9 May 2018 - 11 May 2018, Nanjing, China.

Full text for this resource is not available from the Research Repository.
Item Type: Conference or Workshop Item (Paper)
ISBN: 9781538614822 (online) 9781538614839 (print)
Uncontrolled Keywords: cybersecurity; network intrusion; intrusion detection systems; algorithm; NSL-KDD datasets; OW-ECIDM
Subjects: FOR Classification > 0802 Computation Theory and Mathematics
FOR Classification > 0803 Computer Software
Faculty/School/Research Centre/Department > College of Science and Engineering
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 31 Mar 2019 23:03
Last Modified: 31 Mar 2019 23:03
URI: http://vuir.vu.edu.au/id/eprint/38210
DOI: https://doi.org/10.1109/CSCWD.2018.8465148
ePrint Statistics: View download statistics for this item
Citations in Scopus: 0 - View on Scopus

Repository staff only

View Item View Item

Search Google Scholar