CSE-IDS: Using cost-sensitive deep learning and ensemble algorithms to handle class imbalance in network-based intrusion detection systems

标题
CSE-IDS: Using cost-sensitive deep learning and ensemble algorithms to handle class imbalance in network-based intrusion detection systems
作者
关键词
Network-based intrusion detection system, Cost-sensitive algorithms, Deep learning, Bagging, Boosting, Cybersecurity
出版物
COMPUTERS & SECURITY
Volume 112, Issue -, Pages 102499
出版商
Elsevier BV
发表日期
2021-10-09
DOI
10.1016/j.cose.2021.102499

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Add your recorded webinar

Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.

Upload Now

Become a Peeref-certified reviewer

The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.

Get Started