Utilizando Teoria da Informação para Identificar Conversas de Pedofilia em Redes Sociais de Mensagens Instantâneas

• Juliana G. Postal UFAM/SIDIA
• Eduardo F. Nakamura UFAM

DOI: https://doi.org/10.5753/sbsc.2017.9957

Abstract

Social networks of instant messaging, such as Whatsapp, represent a real threat for children and teenagers, who can easily become targets of sexual predators and pedophiles. Hence, the automatic identification of pedophile chats represent a key tool to protect the young users of social networks. However, these networks have two sensitive particularities: (1) messages are often stored only locally; (2) mobile devices of limited processing power are the major interfaces. In this context, the state-of-the-art has a prohibitive cost to run on mobile devices. On the other hand, the nature of the peer-to-peer communication of such networks make it inviable to process the chat on the cloud, without risking to expose the victims. In this work, we present a new method, based on the Shannon entropy and the Jensen-Shannon divergence, to identify pedophile chats, that achieves nearly 90% of F1 and F0,5, and can be up to 72.8% faster than the state-of-the-art.

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