Identifying human trafficking patterns online


Abstract:

Human trafficking is a major concern worldwide which has evolved with the use of the Internet. Illicit web domains and social networks are used to extend this crime online, where hidden advertisements and messages are used to offer illegal services. The heterogeneity and highly dynamic of these domains impose challenges to information extraction, data mining and machine learning techniques which can be used to identify patterns with relevant information regarding human trafficking on the Internet. This paper summarizes the scope of a doctoral program in informatics at a higher education university. The focus of this research program will be to expand studies on this subject through the analysis of data in the Spanish language, based on different sources of information, such as social media, dark web, and online newspapers to identify patterns related to human trafficking.

Año de publicación:

2017

Keywords:

  • Machine learning
  • human trafficking
  • Data Mining
  • SOCIAL NETWORKS
  • illicit domains
  • information extraction

Fuente:

scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Análisis de redes sociales
  • Minería de datos
  • Ciencia social

Áreas temáticas:

  • Criminología
  • Problemas sociales y servicios a grupos
  • Derecho privado