https://github.com/j0em05/ds.website_pishing_classification
website classification with RandomForestClassifier
https://github.com/j0em05/ds.website_pishing_classification
classification python3 randomforestclassifier
Last synced: 8 months ago
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website classification with RandomForestClassifier
- Host: GitHub
- URL: https://github.com/j0em05/ds.website_pishing_classification
- Owner: j0em05
- Created: 2025-01-30T10:52:53.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-01-30T11:10:14.000Z (9 months ago)
- Last Synced: 2025-03-26T02:11:19.116Z (8 months ago)
- Topics: classification, python3, randomforestclassifier
- Language: Jupyter Notebook
- Homepage:
- Size: 98.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Website pishing classification
This project focuses on classifying websites as phishing, legitimate, or suspicious using machine learning techniques. The goal is to build a model that can accurately detect phishing websites based on various features extracted from their URLs and content.
## dataset
The dataset used in this project is the Phishing Websites Dataset from the UCI Machine Learning Repository https://archive.ics.uci.edu/dataset/327/phishing+websites . This dataset collected mainly from: PhishTank archive, MillerSmiles archive, Google’s searching operators.
## goals
### Goal 1
Develop a machine learning model to accurately classify websites into phishing, legitimate, or suspicious categories.
### Goal 2
Identify the most important features that contribute to the detection of phishing websites.
## Insights
### Insight 1
Features like SSLfinal_State, URL_of_Anchor, and web_traffic are the most significant in distinguishing phishing websites from legitimate ones.
### Insight 2
The Random Forest model achieved an accuracy of 96.81%, demonstrating strong performance in classifying phishing websites.
If you have suggestions or feedback, please contact me in direct message in linkedin and gmail : https://www.linkedin.com/in/ahmad-jumhadi-54a67b223/ and ahmadjumhadi37@gmail.com