C3-Sex: a Chatbot to Chase Cyber Perverts

Abstract

Amongst the myriad of applications of Natural Language Processing (NLP), assisting Law Enforcement Agencies (LEA) in chasing cyber criminals is one of the most recent and promising ones. The paper at hand proposes C^3-Sex, a smart chatbot to interact with suspects in order to profile their interest regarding a given topic. This solution is based on our Artificial Conversational Entity (ACE) that connects to different online chat services to start a conversation regarding a specific matter, in our case child pornography, as this is one sensitive sexual crime that requires special efforts and contributions to be tackled. The ACE was designed using generative and rule-based models in charge of generating the posts and replies constituting the conversation from the chatbot side. The proposed solution also includes a module to analyze the conversations performed by the chatbot and to classify the suspects into three different profiles (indifferent, interested and pervert) according to the responses that they provide in the conversation. Exhaustive experiments were conducted obtaining an initial amount of 320 suspect chats from Omegle, which after filtering were reduced to 35 useful chats, that were classified by C^3-Sex as 26 indifferent, 4 interested and 5 pervert individuals.