Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation
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Title
Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation
Authors
Keywords
Intrusion detection systems, Anomaly detection, Ensemble learners, Combination methods, Tree-based classifier ensemble, Stacking, Systematic mapping study, Empirical review
Journal
Computer Science Review
Volume 39, Issue -, Pages 100357
Publisher
Elsevier BV
Online
2020-12-31
DOI
10.1016/j.cosrev.2020.100357
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- (2019) Abhishek Verma et al. WIRELESS PERSONAL COMMUNICATIONS
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- (2018) Paulo Angelo Alves Resende et al. ACM COMPUTING SURVEYS
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- (2018) Ibrahim Ghafir et al. Future Generation Computer Systems-The International Journal of eScience
- A Detailed Investigation and Analysis of using Machine Learning Techniques for Intrusion Detection
- (2018) Preeti Mishra et al. IEEE Communications Surveys and Tutorials
- DroidDet: Effective and robust detection of android malware using static analysis along with rotation forest model
- (2018) Hui-Juan Zhu et al. NEUROCOMPUTING
- Survey on SDN based network intrusion detection system using machine learning approaches
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- (2018) Shadi Aljawarneh et al. Journal of Computational Science
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- Dimensionality reduction with IG-PCA and ensemble classifier for network intrusion detection
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- A holistic review of Network Anomaly Detection Systems: A comprehensive survey
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- AI-Based Two-Stage Intrusion Detection for Software Defined IoT Networks
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- HFSTE: Hybrid Feature Selections and Tree-Based Classifiers Ensemble for Intrusion Detection System
- (2017) Bayu Adhi TAMA et al. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
- Spatial anomaly detection in sensor networks using neighborhood information
- (2017) Hedde HWJ Bosman et al. Information Fusion
- An in-depth experimental study of anomaly detection using gradient boosted machine
- (2017) Bayu Adhi Tama et al. NEURAL COMPUTING & APPLICATIONS
- Hybridization of computational intelligence methods for attack detection in computer networks
- (2017) A. Branitskiy et al. Journal of Computational Science
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- Industrial Control System Network Intrusion Detection by Telemetry Analysis
- (2016) Stanislav Ponomarev et al. IEEE Transactions on Dependable and Secure Computing
- Ensemble based collaborative and distributed intrusion detection systems: A survey
- (2016) Gianluigi Folino et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Modified parallel random forest for intrusion detection systems
- (2016) Saman Masarat et al. JOURNAL OF SUPERCOMPUTING
- Real time intrusion detection system for ultra-high-speed big data environments
- (2016) M. Mazhar Rathore et al. JOURNAL OF SUPERCOMPUTING
- An effective combining classifier approach using tree algorithms for network intrusion detection
- (2016) Jasmin Kevric et al. NEURAL COMPUTING & APPLICATIONS
- Bagging-TPMiner: a classifier ensemble for masquerader detection based on typical objects
- (2016) Miguel Angel Medina-Pérez et al. SOFT COMPUTING
- Guidelines for conducting systematic mapping studies in software engineering: An update
- (2015) Kai Petersen et al. INFORMATION AND SOFTWARE TECHNOLOGY
- Intrusion detection system: A comprehensive review
- (2012) Hung-Jen Liao et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
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- Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power
- (2009) Salvador García et al. INFORMATION SCIENCES
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