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AI Mule Account Detection System 😱 | Cybersecurity + Machine Learning Fraud Detection Project
This project demonstrates an AI-based Mule Account Detection System built using Machine Learning for cybersecurity applications.
The system helps detect suspicious banking transactions and identifies potential fraud (mule accounts) using predictive AI models.
🔍 Key Features:
✔ Fraud vs Non-Fraud prediction
✔ Machine Learning classification model
✔ CSV file upload for analysis
✔ Risk-based detection system
✔ Streamlit web application interface
🛡️ Domain:
Cybersecurity | Artificial Intelligence | Machine Learning | Financial Fraud Detection
💻 Tech Stack:
Python, Pandas, NumPy, Scikit-learn, Streamlit
🎯 Objective:
To detect mule accounts and prevent financial fraud using AI-driven analysis of transaction data.
⚠️ Disclaimer:
This project is built for educational and hackathon purposes only.
#Cybersecurity #MachineLearning #AIProject #FraudDetection #Hackathon #PythonProject #Streamlit #DataScience #AI
Видео AI Mule Account Detection System 😱 | Cybersecurity + Machine Learning Fraud Detection Project канала Hack & Hash
The system helps detect suspicious banking transactions and identifies potential fraud (mule accounts) using predictive AI models.
🔍 Key Features:
✔ Fraud vs Non-Fraud prediction
✔ Machine Learning classification model
✔ CSV file upload for analysis
✔ Risk-based detection system
✔ Streamlit web application interface
🛡️ Domain:
Cybersecurity | Artificial Intelligence | Machine Learning | Financial Fraud Detection
💻 Tech Stack:
Python, Pandas, NumPy, Scikit-learn, Streamlit
🎯 Objective:
To detect mule accounts and prevent financial fraud using AI-driven analysis of transaction data.
⚠️ Disclaimer:
This project is built for educational and hackathon purposes only.
#Cybersecurity #MachineLearning #AIProject #FraudDetection #Hackathon #PythonProject #Streamlit #DataScience #AI
Видео AI Mule Account Detection System 😱 | Cybersecurity + Machine Learning Fraud Detection Project канала Hack & Hash
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15 июня 2026 г. 13:45:10
00:02:53
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