Framework for a Single Global Repository of Child Abuse Materials

Abstract

Against the tide of a huge amount of data, law enforcement agencies barely manage to focus on undiscovered child abuse materials (CAMs) to identify victims, abusers, and crime scenes. Currently, to alleviate this burden to some extent, there are international and national repositories of CAMs in place, such as Interpol's International Child Sexual Exploitation Database (ICSE DB), NCMEC's Child Recognition and Identification System (CRIS), and the UK's Child Abuse Image Database (CAID). This article introduced these global, regional, and national repositories and other related transnational initiatives comprehensively and also critiques the current trend of setting up more repositories and additional initiatives at local and regional levels. Later, the author elaborates on a plan for a single global repository governed by an international organization. Despite a significant decrease in the costs for a country to be actively involved in the fight against online child sexual abuse and emergence of new possibilities for more effective prevention strategies and investigational methods, such an idea of global centralization might face insurmountable opposition from current stakeholders, particularly because of organizational concerns and technological challenges.

On a global child protection fund financed by international tech companies

“…At the moment, various international and national databases of CSAM co‐exist and this situation generates undesired consequences such as transferring the same images to different databases and compelling countries to spend their already‐constrained budgets to establish a national database. While it is achievable to create a global repository of CSAM with some sizeable modifications, the financial and psychological costs invested by the current parties for many years make it highly inconvenient for them to actively support a plan that might end or significantly diminish their hard‐earned status (Açar, 2020).…”

BS-SC Model: A Novel Method for Predicting Child Abuse Using Borderline-SMOTE Enabled Stacking Classifier

“…The challenges of data storage, retrieval, and analysis can all be addressed with the help of emerging big data technologies. The progress paved the way for the creation of a global repository of child abuse materials [12]. Artificial Intelligence (AI) has similarly cleared the door for the development of rigorous predictive policing frameworks.…”