• CC-DRIVER

Online Child Grooming During the Pandemic from a LEA Perspective



The COVID-19 pandemic has seen internet usage soar, and it has especially affected children and adolescents: on the one hand, schools in many countries had to close and move to remote teaching; on the other, restrictive measures such as lockdowns have as well been imposed globally. This has resulted in a spike of online child abuse and connected issues such as online grooming, posing a challenge to Law Enforcement Agencies (LEAs), and for this reason the second edition of the CC-DRIVER LEA Working Group conference call discussed the topic of online grooming.


CC-DRIVER investigates the human and technical drivers of cybercrime. Our research findings will be translated into a wide range of innovative tools, including cybercrime awareness and investigation tools for law enforcement agencies to strengthen public security and cyber resilience in the European Union. Seven LEAs from four different EU countries (Germany, Greece, Portugal, Spain) and the United Kingdom participated and shared their experiences on this issue.


Given the increasing trend of online grooming, broad attempts to address this issue, with many awareness campaigns being underway in these countries, have been undertaken but there is space for improvement. LEAs can become more important actors in this context by advancing their role as intermediaries.


Direct contact with children and adolescents, mitigation plans for changing behaviour of at-risk individuals, and even mediation programs, are among the best practices shared by the participating police forces.


Another crucial aspect in fighting online grooming is establishing proper data sharing mechanisms for LEAs. In order to achieve this, consistent legal frameworks across the EU are fundamental. This issue, among others, will be addressed in the new Data Governance Act (DGA) proposed by the European Commission. The DGA is designed to facilitate the sharing of data held by public sector agencies, for the benefit of research and, therefore, the greater good. For this purpose it creates a framework for re-using certain categories of public sector data, and encourages the creation of new infrastructure for sharing data laying the foundations for a digital single market of data across EU member states. In addition, data trust models have shown positive results in other areas such as AI and could be useful in this field as well. LEAs need to keep in mind data protection constraints in terms of the Law Enforcement Directive 2016/680 (LED) and adapt the data protection level to the performed activity (investigation, routine procedure, etc.). Regarding AI and Big Data, there was a consensus among the above-mentioned LEA participants on their effectiveness in fighting online grooming, with appropriate safeguards implemented.


According to the experiences reported by the LEAs, ARTEMIS project from Microsoft, ML and AI technologies used by Facebook, and the Sweetie chatbot developed by the NGO Terre des Hommes have proven to be helpful in fighting online grooming and child sexual exploitation.


Finally, it is worth mentioning that there are currently no cases reported on links between online grooming and human trafficking in the above-mentioned countries. This trend, however, can be observed in other countries such as Colombia and the Philippines, where traffickers pose as troubled teenagers in social media just like the teenagers they target, but the LEA participants were not aware of such cases in their respective countries so far.


The next meeting to be held in late May or early June is going to focus on how LEAs can contribute to raising awareness about cybercrime.


If you are an LEA and would like to participate in the next topic for discussion, please write to Valencia Local Police at proyectosplv@valencia.es.

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Abuso infantil en la red durante la pand
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The content of this website reflects only the CC-DRIVER project group’s views. Neither the European Commission nor the Research Executive Agency is liable for any use that may be made of the information contained herein.

This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 883543.

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