Honeypot system for automatic reporting of illegal online gambling sites utilizing SMS Spam

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

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

Abstract

The emergence of illegal online gambling (IOG) has led to an increase in gambling addiction and threats to cyber security. Since IOG is advertised through short message service (SMS), we propose a novel system to detect and extract uniform resource locator (URL) information from SMS spam. For majority of the cases, these URLs are not directly linked to a real website address, which causes difficulties for detection systems. In order to address this problem, we utilized a readable transformation technique (RTT). The resulting suggestions can be enhanced to extract URLs automatically from SMS spam, which will allow local authorities identify and block IOG operations.

Original languageEnglish
Title of host publication2021 World Automation Congress, WAC 2021
PublisherIEEE Computer Society
Pages180-185
Number of pages6
ISBN (Electronic)9781685241117
DOIs
Publication statusPublished - 2021 Aug 1
Event2021 World Automation Congress, WAC 2021 - Virtual, Taipei, Taiwan, Province of China
Duration: 2021 Aug 12021 Aug 5

Publication series

NameWorld Automation Congress Proceedings
Volume2021-August
ISSN (Print)2154-4824
ISSN (Electronic)2154-4832

Conference

Conference2021 World Automation Congress, WAC 2021
Country/TerritoryTaiwan, Province of China
CityVirtual, Taipei
Period21/8/121/8/5

Keywords

  • Binary classification
  • Illegal online gambling, SMS spam, cyber security
  • Machine learning
  • Text mining

ASJC Scopus subject areas

  • Control and Systems Engineering

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