Uncovering Trends in Human Trafficking and Migrant Smuggling Activities: A Natural Language Processing Approach to UNODC SHERLOC Database (original) (raw)
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2020 International Joint Conference on Neural Networks (IJCNN)
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International Journal of General Systems, 2012
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Lecture Notes in Computer Science, 2014
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Lecture Notes in Computer Science, 2008
Recent years have seen an explosion in the number and scale of digital communities (e.g. peer-to-peer file sharing systems, chat applications and social networking sites). Unfortunately, digital communities are host to significant criminal activity including copyright infringement, identity theft and child sexual abuse. Combating this growing level of crime is problematic due to the ever increasing scale of today's digital communities. This paper presents an approach to provide automated support for the detection of child sexual abuse related activities in digital communities. Specifically, we analyze the characteristics of child sexual abuse media distribution in P2P file sharing networks and carry out an exploratory study to show that corpus-based natural language analysis may be used to automate the detection of this activity. We then give an overview of how this approach can be extended to police chat and social networking communities.
Identifying Victims of Human Trafficking at Hotspots by Focusing on People Smuggled to Europe
Research has shown that smuggling of migrants is associated with human trafficking. Hence, victims of human trafficking amongst smuggled migrants should be identified by EU Member States at hotspots established by the European Commission , to overcome the migrant and refugee crisis. Identified victims should be given a visa and a programme of protection to escape their traffickers. In order to achieve these objectives, research suggests that EU law on migrant smuggling should be amended and the Temporary Protection Directive should be applied to smuggled persons when there is an indication that they may be victims of human trafficking. This approach should be adopted by the EASO in cooperation with police forces investigating smuggling and trafficking at hotspots.
Lecture Notes in Computer Science, 2014
Globalization, the ubiquity of mobile communications and the rise of the web have all expanded the environment in which organized criminal entities are conducting their illicit activities, and as a result the environment that law enforcement agencies have to police. This paper triangulates the capability of open-source data analytics, ontological knowledge representation and the wider notion of knowledge management (KM) in order to provide an effective, interdisciplinary means to combat such threats, thus providing law enforcement agencies (LEA's) with a foundation of competitive advantage over human trafficking and other organized crime.
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