2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017, pages 243-248

Anti-fraud system on the basis of data mining technologies

Sapozhnikova M U ¹

Nikonov A.V. ¹

Vulfin A M ¹

Gayanova M M ¹

Mironov Konstantin ¹

Kurennov D V ²

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Department of Computer Science and Robotics, Ufa State Aviation Technical University, Ufa, Russia |

Institute of new materials and technologies, Ural Federal University |

Publication type: Proceedings Article

Publication date: 2017-12-01

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DOI: 10.1109/ISSPIT.2017.8388649

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Abstract

The article is devoted to the issues of increasing the efficiency of transaction monitoring systems (TMS). The main types of TMS with their advantages and disadvantages are considered, and various algorithms of data mining used in this field were also considered. On the basis of the analysis of systems and algorithms, three classifiers were chosen: a multilayer perceptron (MLP), a classifier based on a random forest and a method of support vectors. The selected classifiers were tested on full-scale data. The best indicators were noted for the classifier on the basis of a random forest. The structure of the system for collecting and analyzing information about the user environment (UE) has been developed, which makes it possible to accumulate data about the UE, to mark use cases in manual and automatic modes and to build a database of images for training neural network classifiers. An algorithm for analyzing the information collected about the UE based on cluster analysis is developed.

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Sapozhnikova M. U. et al. Anti-fraud system on the basis of data mining technologies // 2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017. 2017. pp. 243-248.

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Sapozhnikova M. U., Nikonov A., Vulfin A. M., Gayanova M. M., Mironov K., Kurennov D. V. Anti-fraud system on the basis of data mining technologies // 2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017. 2017. pp. 243-248.

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TY - CPAPER

DO - 10.1109/ISSPIT.2017.8388649

UR - https://doi.org/10.1109%2FISSPIT.2017.8388649

TI - Anti-fraud system on the basis of data mining technologies

T2 - 2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017

AU - Sapozhnikova, M U

AU - Nikonov, A.V.

AU - Vulfin, A M

AU - Gayanova, M M

AU - Mironov, Konstantin

AU - Kurennov, D V

PY - 2017

DA - 2017/12/01 00:00:00

SP - 243-248

ER -

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@inproceedings{2017_Sapozhnikova,

author = {M U Sapozhnikova and A.V. Nikonov and A M Vulfin and M M Gayanova and Konstantin Mironov and D V Kurennov},

title = {Anti-fraud system on the basis of data mining technologies},

year = {2017},

pages = {243--248},

month = {dec}

}

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Mironov, Konstantin V