A Consolidated Decision Tree-Based Intrusion Detection System for Binary and Multiclass Imbalanced Datasets
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Title
A Consolidated Decision Tree-Based Intrusion Detection System for Binary and Multiclass Imbalanced Datasets
Authors
Keywords
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Journal
Mathematics
Volume 9, Issue 7, Pages 751
Publisher
MDPI AG
Online
2021-03-31
DOI
10.3390/math9070751
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- (2019) Wenjuan Li et al. Future Generation Computer Systems-The International Journal of eScience
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- Ramp loss K-Support Vector Classification-Regression; a robust and sparse multi-class approach to the intrusion detection problem
- (2017) Seyed Mojtaba Hosseini Bamakan et al. KNOWLEDGE-BASED SYSTEMS
- Modification of supervised OPF-based intrusion detection systems using unsupervised learning and social network concept
- (2017) Hamid Bostani et al. PATTERN RECOGNITION
- Intelligent Electronic Devices with Collaborative Intrusion Detection Systems
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- Toward Bulk Synchronous Parallel-Based Machine Learning Techniques for Anomaly Detection in High-Speed Big Data Networks
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- An effective intrusion detection framework based on MCLP/SVM optimized by time-varying chaos particle swarm optimization
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- Detection of known and unknown DDoS attacks using Artificial Neural Networks
- (2016) Alan Saied et al. NEUROCOMPUTING
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- (2012) Shuo Wang et al. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
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