Credit Card Authentication for Fraud Detection

Abstract

Human face detection is the most promising field of image processing that has a vast area of research oriented real life applications. In the real world the concept is widely used for the content annotation, access control, profiling and potential discrimination in the web world. There is always constructive scope of new inventions in the field of technology which is as vast as galaxy on its own. This leads to the better future. There has been a supportive development in the field of technology by the humans since the beginning of mankind. The motive was in rapid development and also in the advancement of technology to ensure the minimization of risk that is prone along with the new inventions which would make life easier, better and much faster. The main intention of face detection is to find out the human face in the given input. The Psychological process of locating the human face in the visual frame is also possible. Credit cards are widely used all over the world. People mostly use credit cards for huge transactions, as it provides great benefits, hence attract more people. But with these pros, there exists some cons as well, one of them is frauds. The purpose of frauds is to obtain the goods without paying for it. As per the survey, India was ranked among the top 5 companies in credit card frauds. In last 2 years, more than 2000 credit frauds have been filed. The traditional method of credit card transaction uses face and liveness detection for verification.

Country : India

1 Utkarsh Deshpande2 Kaveri More3 Ruchita Sawant4 Archana Avhad5 Prof. Sharad M Rokade

  1. Student, B.E., Computer Engineering, Sir Visvesvaraya Institute of Technology, Nashik, Maharashtra, India
  2. Student, B.E., Computer Engineering, Sir Visvesvaraya Institute of Technology, Nashik, Maharashtra, India
  3. Student, B.E., Computer Engineering, Sir Visvesvaraya Institute of Technology, Nashik, Maharashtra, India
  4. Student, B.E., Computer Engineering, Sir Visvesvaraya Institute of Technology, Nashik, Maharashtra, India
  5. Professor, Computer Engineering, Sir Visvesvaraya Institute of Technology, Nashik, Maharashtra, India

IRJIET, Volume 6, Issue 10, October 2022 pp. 139-141

doi.org/10.47001/IRJIET/2022.610027

References

  1. Method for secure credit card transaction, Nader Nassar, Grant Miller, International Conference, 2013.
  2. Credit card fraud detection based on transaction behaviour, John Richard, Larry A. Vea, TENCON, 2017.
  3. Credit fraud card detection, Andrea, Giacoma, Olivier Cealen, IEEE International Conference, 2018.
  4. Credit card fraudulent Transaction Detection, IEEE International Conference, 2018.
  5. Credit card fraud detection using machine learning, John williams, 7th IEEE International Conference, 2017.
  6. Deep learning detecting fraud in credit card transaction, Abhimanyu Roy, Loreto Alonzi, Peter Beling, System and information, 2018.
  7. Credit card fraud detection system, V. Flilippov, System and information, 2008.
  8. Random forest for credit card fraud detection, Lutao Zheng, Shuo Wang, IEEE 15th International conference, 2018.
  9. Boat adaptive credit card fraud detection System, KK Sherly, IEEE International conference, 2010.
  10. Detecting credit card fraud using periodic features, Alejandro, Bjorn, IEEE International Conference, 2015.
  11. MN BORHAN,” Design of the High Speed and Reliable Source Coupled Logic Multiplexer”, Journal of VLSI Circuits and Systems 1 (01), 18-22, 2019.
  12. Mv Ngo Tien Ho, “A High Speed and Reliable Double Edge Triggered D- Flip-Flop for Memory Applications”, Journal of VLSI Circuits and Systems, 1 (01), 13-17, 2019.