Evaluating machine learning algorithms for intrusion detection systems using the dataset CIDDS-002-Reference-Cited by-同舟云学术

Evaluating machine learning algorithms for intrusion detection systems using the dataset CIDDS-002

Published:2021-10-22 Issue: Volume: Page:
ISSN:
Container-title:2021 4th International Conference on Computer Science and Software Engineering (CSSE 2021)
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Author:

Dang Quang-Vinh¹

Affiliation:

1. Industrial University of Ho Chi Minh city, Vietnam

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3494885.3494906

Reference22 articles.

1. On the Performance of Machine Learning Models for Anomaly-Based Intelligent Intrusion Detection Systems for the Internet of Things

2. A survey of intrusion detection systems based on ensemble and hybrid;Aburomman Abdulla Amin;Learning,1999

3. Comparison between XGBoost, LightGBM and CatBoost using a home credit dataset;Al Daoud Essam;International Journal of Computer and Information Engineering,2019

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3. Research and Implementation of Industrial Control Network Security Intrusion Detection Classification based on Deep Learning;2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC);2022-06-17

4. Intrusion Detection in Internet of Things Environment;Advances in Digital Science - ADS 2022;2022