TY - GEN
T1 - A statistical approach towards fraud detection in the horse racing
AU - Min, Moohong
AU - Lee, Jemin Justin
AU - Park, Hyunbeom
AU - Shin, Hyojoung
AU - Lee, Kyungho
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Anomaly detection
KW - Big data
KW - Fraud detection
KW - Horse racing
KW - Horse racing information security
KW - IoT (Internet of Things) based applications
UR - http://www.scopus.com/inward/record.url?scp=85098250460&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098250460&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-65299-9_15
DO - 10.1007/978-3-030-65299-9_15
M3 - Conference contribution
AN - SCOPUS:85098250460
SN - 9783030652982
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 191
EP - 202
BT - Information Security Applications - 21st International Conference, WISA 2020, Revised Selected Papers
A2 - You, Ilsun
PB - Springer Science and Business Media Deutschland GmbH
T2 - 21st International Conference on Information Security Applications, WISA 2020
Y2 - 26 August 2020 through 28 August 2020
ER -