Development of Hybrid Intrusion Detection System Leveraging Ensemble Stacked Feature Selectors and Learning Classifiers to Mitigate the DoS Attacks
Abstract Denial of service (DoS) attacks occur more frequently with the progressive development of the Internet of things (IoT) and other Internet-based communication technologies. Since these technologies are deeply rooted in the individual’s comfort life, protecting the user’s privacy and security...
Saved in:
Main Authors: | P. Mamatha, S. Balaji, S. Sai Anuraghav |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer
2025-02-01
|
Series: | International Journal of Computational Intelligence Systems |
Subjects: | |
Online Access: | https://doi.org/10.1007/s44196-025-00750-6 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
DESIGN ANALYSIS OF AN AUTOMATIC PHASE SELECTOR
by: ADEDOTUN O. OWOJORI, et al.
Published: (2022-01-01) -
HSTCN-NuSVC: A Homogeneous Stacked Deep Ensemble Learner for Classifying Human Actions Using Smartphones
by: Sarmela Raja Sekaran, et al.
Published: (2025-02-01) -
Identification of multiple power quality disturbances in hybrid microgrid using deep stacked auto-encoder based bi-directional LSTM classifier
by: Ravi Kumar Jalli, et al.
Published: (2025-03-01) -
A Novel Ensemble Classifier Selection Method for Software Defect Prediction
by: Xin Dong, et al.
Published: (2025-01-01) -
Attack Level of Brown Planthopper Nilaparvata lugens Stal (Hemiptera: Delphacidae) on Varieties of Rice from Pasaman in Greenhouse
by: Eva Zulaikha, et al.
Published: (2021-07-01)