A statistical approach towards fraud detection in the horse racing

Moohong Min, Jemin Justin Lee, Hyunbeom Park, Hyojoung Shin, Kyungho Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the inception of online betting in S. Korea, various foreigner professional gambling groups have exploited the betting regulations. This phenomenon has occurred mainly in Asia, because the regulations on gambling in these countries are complex and robust. Our study focuses on the horse racing in S. Korea, which is operated under the government funding. The foreigner gambling groups tried unlimited betting by modifying the official IoT (Internet of Things) based APP arbitrarily. We have checked that some abnormal transactions can occur by modifying this application. Our study proposes a fraud detection method that can help detecting abnormal activities and prevent them. Currently, the Korea Racing Authority (KRA) has been criticized for being ill-equipped to detect abnormal activities with the Walkerhill Incident. Our study presents a new anomaly detection model that uses a flexible window. In this study, we propose an idea that aims to detect abnormal betting transactions.

Original languageEnglish
Title of host publicationInformation Security Applications - 21st International Conference, WISA 2020, Revised Selected Papers
EditorsIlsun You
PublisherSpringer Science and Business Media Deutschland GmbH
Pages191-202
Number of pages12
ISBN (Print)9783030652982
DOIs
Publication statusPublished - 2020
Event21st International Conference on Information Security Applications, WISA 2020 - Jeju Island, Korea, Republic of
Duration: 2020 Aug 262020 Aug 28

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12583 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Information Security Applications, WISA 2020
CountryKorea, Republic of
CityJeju Island
Period20/8/2620/8/28

Keywords

  • Anomaly detection
  • Big data
  • Fraud detection
  • Horse racing
  • Horse racing information security
  • IoT (Internet of Things) based applications

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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