# A Decision-Fusion-Based Ensemble Approach for Malicious Websites Detection
## 3 Materials and Methods
### Methodology of Proposed Approach
#### 3.2.1 Gradient-Boosting (GB) Classifier Method
* [PERSON] and [PERSON] (2018) [PERSON]; [PERSON] Malicious URLs detection using decision tree classifiers and majority voting technique. _Cybern. Inf. Technol._**2018**, _18_, 11-29. [CrossRef]
* [PERSON] and [PERSON] (2020) [PERSON]; [PERSON] A Convolutional Neural Network Model to Detect Illegitimate URLs. In Proceedings of the 2020 11 th International Conference on Information and Communication Systems (ICICS), Irbid, Jordan, 7-9 April 2020; pp. 220-225. * [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON] Two phase classification model to detect malicious URLs. _Int. J. Appl. Eng. Res._**2017**, _12_, 1893-1898. * [PERSON] and [PERSON] (2022) [PERSON]; [PERSON] Intelligent Phishing Website Detection using Deep Learning. In Proceedings of the 2022 8 th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 25-26 March 2022; pp. 1741-1745. * [PERSON] et al. (2018) [PERSON]; [PERSON]; [PERSON] Klasifikasi Malicious Websites Menggunakan Algoritma K-NN Berdasarkan Application Layers dan Network Characteristics. _Cogfto Smart J._**2018**, \(4\), 37-45. [CrossRef]
* [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON] Detecting Malicious URL. In Proceedings of the 2020 International Conference on Computing and Information Technology (ICCIT-1441), Tabuk, Saudi Arabia, 9-10 September 2020; pp. 1-5. * [PERSON] et al. (2020) [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] Creation of a fuzzy model for verification of malicious sites based on fuzzy neural networks. _Int. J. Eng. Res. Technol._**2020**, _13_, 4432-4438. * [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON] Rakshanet: Url-Aware Malicious Website Classifier. In Proceedings of the 2021 2 nd International Conference on Secure Cyber Computing and Communications (ICSCCC), Jalandhar, India, 21-23 May 2021; pp. 308-313. * [PERSON] and [PERSON] (2021) [PERSON]; [PERSON] Malicious URL Detection using Multilayer CNN. In Proceedings of the 2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3 ICT), Zallaq, Bahrain, 29-30 September 2021; pp. 340-345. * [PERSON] et al. (2022) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] An assessment of lexical, network, and content-based features for detecting malicious urls using machine learning and deep learning models. _Comput. Intell. Neurosci._**2022**, _2022_, 3241216. [CrossRef]
* [PERSON] and [PERSON] (2022) [PERSON]; [PERSON] Machine Learning-Based Effective Malicious Web Page Detection. _Int. J. Inf. Secur. Sci._**2022**, _11_, 28-39. * [PERSON] (2001) [PERSON] Greedy function approximation: A gradient boosting machine. _Ann. Stat._**2001**, _29_, 1189-1232. [CrossRef]
* [PERSON] et al. (2008) [PERSON]; [PERSON]; [PERSON] A working guide to boosted regression trees. _J. Anim. Ecol._**2008**, _77_, 802-813. [CrossRef] [PubMed]
* [PERSON] et al. (1999) [PERSON]; [PERSON]; [PERSON] A short introduction to boosting. _J.-Jpn. Soc. Artif. Intell._**1999**, _14_, 771-780. * [PERSON] et al. (2011) [PERSON]; [PERSON] [PERSON]; [PERSON] Predicting disease risks from highly imbalanced data using random forest. _BMC Med. Inform. Decis. Mak._**2011**, _11_, 51. [CrossRef]
* [PERSON] (2009) [PERSON] Balanced gradient boosting from imbalanced data for clinical outcome prediction. _Stat. Appl. Genet. Mol. Biol._**2009**, \(8\), 20. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Xgboost: Extreme gradient boosting. _R Package Version 0.4-2_**2015**, \(1\), 1-4. * [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities. _Inf. Fusion_**2020**, _64_, 205-237. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON] A comparative analysis of gradient boosting algorithms. _Artif. Intell.