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A Darknet Traffic Detector Using Bayesian Optimized and Cost-Sensitive Extreme Gradient Boosting

https://doi.org/10.2139/ssrn.4678907
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/ett.4150openalex-extracted
Network intrusion detection system: A systematic study of machine learning and deep learning approaches
inferredcites →https://doi.org/10.1016/j.elerap.2017.06.004openalex-extracted
Cost-sensitive boosted tree for loan evaluation in peer-to-peer lending
inferredcites →https://doi.org/10.1016/j.iswa.2023.200199openalex-extracted
Darknet traffic detection and characterization with models based on decision trees and neural networks
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-extracted
Random Forests
inferredcites →https://doi.org/10.1023/a:1012771025575openalex-extracted
A Taxonomy of Global Optimization Methods Based on Response Surfaces
inferredcites →https://doi.org/10.1109/access.2021.3105000openalex-extracted
DarkDetect: Darknet Traffic Detection and Categorization Using Modified Convolution-Long Short-Term Memory
inferredcites →https://doi.org/10.1109/access.2022.3168857openalex-extracted
Business Failure Prediction Based on a Cost-Sensitive Extreme Gradient Boosting Machine
inferredcites →https://doi.org/10.1109/comst.2015.2497690openalex-extracted
Darknet as a Source of Cyber Intelligence: Survey, Taxonomy, and Characterization
inferredcites →https://doi.org/10.1109/ecai52376.2021.9515039openalex-extracted
A Machine Learning Approach to Classify Network Traffic
inferredcites →https://doi.org/10.1109/iccsce50387.2020.9204948openalex-extracted
Cost-Sensitive Extreme Gradient Boosting for Imbalanced Classification of Breast Cancer Diagnosis
inferredcites →https://doi.org/10.1109/tpami.2010.71openalex-extracted
Cost-Sensitive Boosting
inferredcites →https://doi.org/10.1145/2939672.2939785openalex-extracted
XGBoost
inferredcites →https://doi.org/10.1145/3442520.3442521openalex-extracted
DIDarknet: A Contemporary Approach to Detect and Characterize the Darknet Traffic using Deep Image Learning
inferredcites →https://doi.org/10.1145/502034openalex-extracted
Proceedings of the eighteenth ACM symposium on Operating systems principles
inferredcites →https://doi.org/10.1613/jair.953openalex-extracted
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.21236/ada465464openalex-extracted
Tor: The Second-Generation Onion Router
inferredcites →https://doi.org/10.3390/electronics11040556openalex-extracted
Machine-Learning-Based Darknet Traffic Detection System for IoT Applications
inferredcites →https://doi.org/10.4230/oasics.dx.2024.27openalex-extracted
On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-extracted
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.48550/arxiv.1206.2944openalex-extracted
Practical Bayesian Optimization of Machine Learning Algorithms
inferredcites →https://doi.org/10.48550/arxiv.1705.07874openalex-extracted
A Unified Approach to Interpreting Model Predictions
inferredcites →https://doi.org/10.48550/arxiv.2104.10201openalex-extracted
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
inferredcites →https://doi.org/10.5220/0005740704070414openalex-extracted
Characterization of Encrypted and VPN Traffic using Time-related Features
inferredcites →https://doi.org/10.5220/0006105602530262openalex-extracted
Characterization of Tor Traffic using Time based Features
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