During the past decade, the technological advancement have allowed the gambling industry worldwide to deploy various platforms such as the web and mobile applications. Govern-ment agencies and local authorities have place strict regulations regarding the location and amount allowed for gambling. These efforts are made to prevent gambling addictions and monitor fraud-ulent activities. The revenue earned from gambling provides a considerable amount of tax revenue. The inception of internet gambling have allowed professional gamblers to par take in unlawful acts. However, the lack of studies on the technical inspections and systems to prohibit unlawful internet gambling has caused incidents such as the Walkerhill Hotel incident in 2016, where fraudsters placed bets abnormally by modifying an Internet of Things (IoT)-based application called “MyCard”. This paper investigates the logic used by smartphone IoT applications to vali-date the location of users and then confirm continuous threats. Hence, our research analyzed transactions made on applications that operated using location authentication through IoT devices. Drawing on gambling transaction data from the Korea Racing Authority, this research used time series machine learning algorithms to identify anomalous activities and transactions. In our re-search, we propose a method to detect and prevent these anomalies by conducting a comparative analysis of the results of existing anomaly detection techniques and novel techniques.
Bibliographical noteFunding Information:
Funding: This research was funded by Agency for Defense Development grant number UD190016ED.
Acknowledgements: This research was funded by Agency for Defense Development grant number UD190016ED. This research was supported by the Korea Racing Authority.
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
- Anomaly detection
- Big data
- Cyber security
- Horse racing
- Internet of Things
- Machine learning
- Mobile sensors
- Time series data
- Transaction data
ASJC Scopus subject areas
- Analytical Chemistry
- Atomic and Molecular Physics, and Optics
- Electrical and Electronic Engineering