PhishGuard for RQ1 Dissertation

rq01binus.inarlabs.net

Main

Dashboard Dataset & Cleaning Feature Extraction Taksonomi URL Eksperimen

Hasil

Hasil & Tabel Visualisasi Confusion Matrix Analisis RQ Feature Selection & RR Download

Sistem

Settings

PhishGuard v2.0 — Flask

Jalankan Eksperimen

Pilih kombinasi Feature Selection × Redundancy Reduction × Classifier

Status Dataset

Dataset yang dijalankan

Dataset belum diupload. Buka menu Dataset & Cleaning terlebih dahulu.

1. Feature Selection

Pilih minimal 1

SHAP

Lundberg & Lee (2017) NeurIPS — https://doi.org/10.48550/arX

mRMR

Ding & Peng (2005) IEEE TCBB — https://doi.org/10.1109/TCBB.

Boruta

Kursa & Rudnicki (2010) JSS — https://doi.org/10.18637/jss.v

LASSO

Tibshirani (1996) JRSS-B — https://doi.org/10.1111/j.2517-61

Chi2

Liu & Setiono (1995) ICML — https://dl.acm.org/doi/10.5555/3

2. Redundancy Reduction

Pilih minimal 1

Pearson

Hall (1999) FLAIRS — Correlation-based Feature Subset Select

VIF

Belsley et al. (1980) Wiley — https://doi.org/10.1002/047172

PCA

Jolliffe (2002) Springer — https://doi.org/10.1007/b98835

Autoencoder

Hinton & Salakhutdinov (2006) Science — https://doi.org/10.1

MIC

Reshef et al. (2011) Science — https://doi.org/10.1126/scien

3. ML Classifier

Pilih minimal 1

Breiman (2001) Machine Learning — https://doi.org/10.1023/A:

XGBoost

Chen & Guestrin (2016) KDD — https://doi.org/10.1145/2939672

SVM

Cortes & Vapnik (1995) Machine Learning — https://doi.org/10

LightGBM

Ke et al. (2017) NeurIPS

MLP

Rumelhart et al. (1986) Nature — https://doi.org/10.1038/323

Parameter Eksperimen

Train Size

Test Size

K-Fold

N Features FS

Random Seed

Sample Size (0 = semua URL)

Ubah parameter lain di menu Settings

125

kombinasi akan dijalankan

5 FS × 5 RR × 5 Clf

Progress Eksperimen

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