https://github.com/projects-developer/online-payment-fraud-detection-using-machine-learning
ONLINE PAYMENT FRAUD DETECTION USING MACHINE LEARNING Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials
https://github.com/projects-developer/online-payment-fraud-detection-using-machine-learning
bca-projects btech-projects computer-science-projects computerscienceprojects final-year-projects finalyearprojects machine-learning mca-project mtech-projects online-payment online-payment-fraud-detection paymentsecurity
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ONLINE PAYMENT FRAUD DETECTION USING MACHINE LEARNING Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials
- Host: GitHub
- URL: https://github.com/projects-developer/online-payment-fraud-detection-using-machine-learning
- Owner: Projects-Developer
- Created: 2025-02-14T11:24:33.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-14T11:28:25.000Z (about 1 year ago)
- Last Synced: 2025-02-14T12:30:27.317Z (about 1 year ago)
- Topics: bca-projects, btech-projects, computer-science-projects, computerscienceprojects, final-year-projects, finalyearprojects, machine-learning, mca-project, mtech-projects, online-payment, online-payment-fraud-detection, paymentsecurity
- Homepage: https://www.finalproject.in
- Size: 2.93 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ONLINE PAYMENT FRAUD DETECTION USING MACHINE LEARNING
ONLINE PAYMENT FRAUD DETECTION USING MACHINE LEARNING
### Abstract
Online payment fraud has become a significant concern in the digital age. Machine learning (ML) can play a crucial role in detecting and preventing such fraudulent activities. This approach involves training ML algorithms on historical data to identify patterns and anomalies indicative of fraudulent transactions.
By leveraging features such as transaction amount, location, and user behavior, ML models can accurately classify transactions as legitimate or fraudulent. Techniques like supervised learning, clustering, and neural networks can be employed to develop effective fraud detection systems.
The integration of ML in online payment systems can help reduce false positives, improve detection accuracy, and enhance overall security. By staying one step ahead of fraudsters, ML-powered fraud detection can protect consumers and businesses from financial losses.
### Keywords
Online payment fraud, Machine learning, Fraud detection, Payment security, Transaction analysis, Anomaly detection, Supervised learning, Clustering, Neural networks, Cybersecurity
### Project include:
1. Synopsis
2. PPT
3. Research Paper
4. Code
5. Explanation video
6. Documents
7. Report
### Need Code, Documents & Explanation video ?
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