Quarterly Publication

Document Type : Original Article

Authors

1 Department of Computer Science and Engineering, OEC Engineering College, OD, India.

2 Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, AP, India.

3 Government Information Headquarters Inspur Software Group Company Ltd, Jinan, China.

10.22105/bdcv.2021.142231

Abstract

Every year, millions of dollars are lost due to fraudulent credit card transactions. To help fraud investigators, more algorithms are turning to powerful machine learning methodologies. Designing fraud detection algorithms is particularly difficult because to the non-stationary distribution of data, excessively skewed class distributions, and continuous streams of transactions. At the same time, due to confidentiality considerations, public data is uncommon, leaving many questions unanswered about the best technique for dealing with them. We present some replies from the practitioners in this publication. Un balanced ness, non- stationarity and assessment. Our industrial partner provided us with an actual credit card dataset, which we used to do the analysis. In this project, we attempt to develop and evaluate a model for the imbalanced credit card fraud dataset.

Keywords

  1. Mohapatra, H., & Rath, A. K. (2020). Fundamentals of software engineering: designed to provide an insight into the software engineering concepts. BPB Publications.
  2. Mohapatra, H., Debnath, S., & Rath, A. K. (2019). Energy management in wireless sensor network through EB-LEACH. International journal of research and analytical reviews (IJRAR), 56-61. https://easychair.org/publications/preprint_download/tf5s
  3. Mohapatra, H., Debnath, S., Rath, A. K., Landge, P. B., Gayen, S., & Kumar, R. (2020). An efficient energy saving scheme through sorting technique for wireless sensor network. International journal8(8), 4278-4286.
  4. Mohapatra, H., Rath, A. K., Landge, P. B., Bhise, D. H. I. R. A. J., Panda, S., & Gayen, S. A. (2020). A comparative analysis of clustering protocols of wireless sensor network. International journal of mechanical and production engineering research and development (IJMPERD) ISSN (P)10(3), 2249-6890.
  5. Mohapatra, H., & Rath, A. K. (2019). Fault tolerance through energy balanced cluster formation (EBCF) in WSN. Smart innovations in communication and computational sciences(pp. 313-321). Springer, Singapore.
  6. Mohapatra, H., & Rath, A. K. (2019). Fault tolerance in WSN through PE-LEACH protocol. IET wireless sensor systems9(6), 358-365.
  7. Mohapatra, H., & Rath, A. K. (2021). Fault tolerance in WSN through uniform load distribution function. International journal of sensors wireless communications and control11(4), 385-394.
  8. Mohapatra, H., & Rath, A. K. (2019). Fault-tolerant mechanism for wireless sensor network. IET wireless sensor systems10(1), 23-30.
  9. Mohapatra, H., & Rath, A. K. (2020). Survey on fault tolerance-based clustering evolution in WSN. IET networks9(4), 145-155.
  10. Mohapatra, H., Rath, A. K., Lenka, R. K., Nayak, R. K., & Tripathy, R. (2021). Topological localization approach for efficient energy management of WSN. Evolutionary intelligence, 1-11. https://link.springer.com/article/10.1007/s12065-021-00611-z
  11. Mohapatra, H., Rath, S., Panda, S., & Kumar, R. (2020). Handling of man-in-the-middle attack in wsn through intrusion detection system. International journal8(5), 1503-1510.
  12. Mohapatra, H. (2021). Designing of fault tolerant models for wireless sensor network (Ph.D Dissertation, Veer Surendra Sai University of Technology). Retrieved from http://hdl.handle.net/10603/333160
  13. Nirgude, V., Mahapatra, H., & Shivarkar, S. (2017). Face recognition system using principal component analysis & linear discriminant analysis method simultaneously with 3d morphable model and neural network BPNN method. Global journal of advanced engineering technologies and sciences4(1), 1-6.
  14. Mohapatra, H. (2009). HCR by using neural network (Master's Thesis, M. Tech_s Desertion, Govt. College of Engineering and Technology, Bhubaneswar).
  15. Mohapatra, H., & Rath, A. K. (2021). A fault tolerant routing scheme for advanced metering infrastructure: an approach towards smart grid. Cluster computing, 24, 2193-2211.
  16. Panda, M., Pradhan, P., Mohapatra, H., & Barpanda, N. K. (2019). Fault tolerant routing in heterogeneous environment. International journal of scientific & technology research8(8), 1009-1013.
  17. Ande, V. K., & Mohapatra, H. (2015). SSO mechanism in distributed environment. International journal of innovations & advancement in computer science, 4(6), 133-136.
  18. Kumar, R., Jha, S., & Singh, R. (2020). A different approach for solving the shortest path problem under mixed fuzzy environment. International journal of fuzzy system applications (IJFSA)9(2), 132-161.
  19. Broumi, S., Dey, A., Talea, M., Bakali, A., Smarandache, F., Nagarajan, D., ... & Kumar, R. (2019). Shortest path problem using Bellman algorithm under neutrosophic environment. Complex & intelligent systems5(4), 409-416.
  20. Mohapatra, H. (2018). C Programming: Practice cpp. Kindle Edition.
  21. Kumar, R., Dey, A., Broumi, S., & Smarandache, F. (2020). A study of neutrosophic shortest path problem. Neutrosophic graph theory and algorithms(pp. 148-179). IGI Global.
  22. Kumar, R., Edalatpanah, S. A., Jha, S., & Singh, R. (2019). A novel approach to solve gaussian valued neutrosophic shortest path problems. Infinite study.
  23. Kumar, R., Edaltpanah, S. A., Jha, S., Broumi, S., & Dey, A. (2018). Neutrosophic shortest path problem. Infinite Study.
  24. Kumar, R., Edalatpanah, S. A., & Mohapatra, H. (2020). Note on “Optimal path selection approach for fuzzy reliable shortest path problem”. Journal of intelligent & fuzzy systems, (Preprint), 39(5), 7653-7656.
  25. Kumar, R., Edalatpanah, S., Jha, S., Broumi, S., Singh, R., & Dey, A. A. (2019). Multi objective programming approach to solve integer valued neutrosophic shortest path problems. Neutrosophic sets and systems, 24, 134-154.
  26. Kumar, R., Edalatpanah, S. A., Jha, S., & Singh, R. (2019). A Pythagorean fuzzy approach to the transportation problem. Complex & intelligent systems5(2), 255-263.
  27. Pratihar, J., Kumar, R., Dey, A., & Broumi, S. (2020). Transportation problem in neutrosophic environment. Neutrosophic graph theory and algorithms(pp. 180-212). IGI Global.
  28. Pratihar, J., Kumar, R., Edalatpanah, S. A., & Dey, A. (2021). Modified Vogel’s approximation method for transportation problem under uncertain environment. Complex & intelligent systems7(1), 29-40.
  29. Gayen, S., Jha, S., Singh, M., & Kumar, R. (2019). On a generalized notion of anti-fuzzy subgroup and some characterizations. International journal of engineering and advanced technology8(3), 385-390.
  30. Gayen, S., Smarandache, F., Jha, S., & Kumar, R. (2020). Interval-valued neutrosophic subgroup based on interval-valued triple t-norm. Neutrosophic sets in decision analysis and operations research(pp. 215-243). IGI Global.
  31. Gayen, S., Smarandache, F., Jha, S., & Kumar, R. (2020). Introduction to interval-valued neutrosophic subring(Vol. 36). Infinite Study.
  32. Gayen, S., Smarandache, F., Jha, S., Singh, M. K., Broumi, S., & Kumar, R. (2020). Introduction to plithogenic hypersoft subgroup. Neutrosophic sets and system, 33, 14-22.
  33. Gayen, S., Smarandache, F., Jha, S., Singh, M. K., Broumi, S., & Kumar, R. (2020). Introduction to plithogenic subgroup. Neutrosophic graph theory and algorithms(pp. 213-259). IGI Global.
  34. Gayen, S., Smarandache, F., Jha, S., Singh, M. K., Broumi, S., & Kumar, R. (2020). Soft subring theory under interval-valued neutrosophic environment(Vol. 36). Infinite Study.
  35. Kumar, R., Edalatpanah, S. A., Jha, S., Gayen, S., & Singh, R. (2019). Shortest path problems using fuzzy weighted arc length. International journal of innovative technology and exploring engineering8(6), 724-731.
  36. Kumar, R., Jha, S., & Singh, R. (2017). Shortest path problem in network with type-2 triangular fuzzy arc length. Journal of applied research on industrial engineering4(1), 1-7.
  37. Mohapatra, H., Panda, S., Rath, A., Edalatpanah, S., & Kumar, R. (2020). A tutorial on powershell pipeline and its loopholes. International journal of emerging trends in engineering research8(4), 975-982.
  38. Kumar, R., Edalatpanah, S. A., Gayen, S., & Broum, S. (2021). Answer Note “A novel method for solving the fully neutrosophic linear programming problems: Suggested modifications”. Neutrosophic sets and systems39(1), 148-152. https://digitalrepository.unm.edu/cgi/viewcontent.cgi?article=1751&context=nss_journal
  39. Panda, H., Mohapatra, H., & Rath, A. K. (2020). WSN-based water channelization: an approach of smart water. Smart cities—opportunities and challenges58, 157-166.
  40. Mohapatra, H., & Rath, A. K. (2020, October). Nub less sensor based smart water tap for preventing water loss at public stand posts. 2020 IEEE microwave theory and techniques in wireless communications (MTTW)(Vol. 1, pp. 145-150). IEEE.
  41. Rout, S. S., Mohapatra, H., Nayak, R. K., Tripathy, R., Bhise, D., Patil, S. P., & Rath, A. K. (2020). Smart water solution for monitoring of water usage based on weather condition. International journal8(9), 5335-5343.
  42. Mohapatra, H., & Rath, A. K. (2021). IoE based framework for smart agriculture. Journal of ambient intelligence and humanized computing, 1-18. https://doi.org/10.1007/s12652-021-02908-4
  43. Mohapatra, H., & Rath, A. K. (2021). An IoT based efficient multi-objective real-time smart parking system. International journal of sensor networks37(4), 219-232.
  44. Mohapatra, H., & Rath, A. K. (2019). Detection and avoidance of water loss through municipality taps in India by using smart taps and ICT. IET wireless sensor systems9(6), 447-457.
  45. Mohapatra, H. (2020). Offline drone instrumentalized ambulance for emergency situations. IAES International journal of robotics and automation9(4), 251-255