Data Mining based Framework for Effective Intrusion Detection using Hybrid Feature Selection Approach-Reference-Cited by-同舟云学术

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Data Mining based Framework for Effective Intrusion Detection using Hybrid Feature Selection Approach

Published:2019-08-08 Issue:8 Volume:11 Page:1-12
ISSN:2074-9090
Container-title:International Journal of Computer Network and Information Security
language:
Short-container-title:IJCNIS

Author:

Manjunatha B.A., ,Gogoi Prasanta,Akkalappa M. T.

Publisher

MECS Publisher

Subject

Applied Mathematics,Computer Networks and Communications,Computer Science Applications,Safety Research,Information Systems,Software

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Intelligent Identification of Electricity Stealing Based on the Correlation of Line Loss;2022 7th Asia Conference on Power and Electrical Engineering (ACPEE);2022-04

2. The Hybrid Detection Methodology of Attacks for 5G;Advances in Artificial Systems for Power Engineering II;2022

3. Application Data Mining Technology in Monitoring Strategies of College Students' English Learning Motivation;2021 4th International Conference on Information Systems and Computer Aided Education;2021-09-24

4. Improving the Performance of Machine Learning-Based Network Intrusion Detection Systems on the UNSW-NB15 Dataset;Computational Intelligence and Neuroscience;2021-06-15

5. Intelligent Detection of Electricity Stealing by Replacing Instrument Transformer Based on Daily Load Date Mining;Advances in Intelligent Systems and Computing;2021

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