<i>C</i><sup>3</sup>-Sex: A Conversational Agent to Detect Online Sex Offenders
Prevention of cybercrime is one of the missions of Law Enforcement Agencies (LEA) aiming to protect and guarantee sovereignty in the cyberspace. In this regard, online sex crimes are among the principal ones to prevent, especially those where a child is abused. The paper at hand proposes <inline-...
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doaj-8ef5206f17f841089655b536ddd0cdc02020-11-25T03:58:31ZengMDPI AGElectronics2079-92922020-10-0191779177910.3390/electronics9111779<i>C</i><sup>3</sup>-Sex: A Conversational Agent to Detect Online Sex OffendersJohn Ibañez Rodríguez0Santiago Rocha Durán1Daniel Díaz-López2Javier Pastor-Galindo3Félix Gómez Mármol4Faculty of Computer Engineering, Escuela Colombiana de Ingeniería Julio Garavito, AK.45 No.205-59, Bogotá 111166, ColombiaFaculty of Computer Engineering, Escuela Colombiana de Ingeniería Julio Garavito, AK.45 No.205-59, Bogotá 111166, ColombiaSchool of Engineering, Science and Technology, Universidad del Rosario, Carrera 6 No. 12 C-16, Bogotá 111711, ColombiaFaculty of Computer Science, Campus de Espinardo, University of Murcia, 30100 Murcia, SpainFaculty of Computer Science, Campus de Espinardo, University of Murcia, 30100 Murcia, SpainPrevention of cybercrime is one of the missions of Law Enforcement Agencies (LEA) aiming to protect and guarantee sovereignty in the cyberspace. In this regard, online sex crimes are among the principal ones to prevent, especially those where a child is abused. The paper at hand proposes <inline-formula><math display="inline"><semantics><msup><mi>C</mi><mn>3</mn></msup></semantics></math></inline-formula>-Sex, a smart chatbot that uses Natural Language Processing (NLP) to interact with suspects in order to profile their interest regarding online child sexual abuse. This solution is based on our Artificial Conversational Entity (ACE) that connects to different online chat services to start a conversation. The ACE is designed using generative and rule-based models in charge of generating the posts and replies that constitute the conversation from the chatbot side. The proposed solution also includes a module to analyze the conversations performed by the chatbot and calculate a set of 25 features that describes the suspect’s behavior. After 50 days of experiments, the chatbot generated a dataset with 7199 profiling vectors with the features associated to each suspect. Afterward, we applied an unsupervised method to describe the results that differentiate three groups, which we categorize as indifferent, interested, and pervert. Exhaustive analysis is conducted to validate the applicability and advantages of our solution.https://www.mdpi.com/2079-9292/9/11/1779chatbotonline child sexual abusecriminal profilingnatural language processinglaw enforcement agencies |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
John Ibañez Rodríguez Santiago Rocha Durán Daniel Díaz-López Javier Pastor-Galindo Félix Gómez Mármol |
spellingShingle |
John Ibañez Rodríguez Santiago Rocha Durán Daniel Díaz-López Javier Pastor-Galindo Félix Gómez Mármol <i>C</i><sup>3</sup>-Sex: A Conversational Agent to Detect Online Sex Offenders Electronics chatbot online child sexual abuse criminal profiling natural language processing law enforcement agencies |
author_facet |
John Ibañez Rodríguez Santiago Rocha Durán Daniel Díaz-López Javier Pastor-Galindo Félix Gómez Mármol |
author_sort |
John Ibañez Rodríguez |
title |
<i>C</i><sup>3</sup>-Sex: A Conversational Agent to Detect Online Sex Offenders |
title_short |
<i>C</i><sup>3</sup>-Sex: A Conversational Agent to Detect Online Sex Offenders |
title_full |
<i>C</i><sup>3</sup>-Sex: A Conversational Agent to Detect Online Sex Offenders |
title_fullStr |
<i>C</i><sup>3</sup>-Sex: A Conversational Agent to Detect Online Sex Offenders |
title_full_unstemmed |
<i>C</i><sup>3</sup>-Sex: A Conversational Agent to Detect Online Sex Offenders |
title_sort |
<i>c</i><sup>3</sup>-sex: a conversational agent to detect online sex offenders |
publisher |
MDPI AG |
series |
Electronics |
issn |
2079-9292 |
publishDate |
2020-10-01 |
description |
Prevention of cybercrime is one of the missions of Law Enforcement Agencies (LEA) aiming to protect and guarantee sovereignty in the cyberspace. In this regard, online sex crimes are among the principal ones to prevent, especially those where a child is abused. The paper at hand proposes <inline-formula><math display="inline"><semantics><msup><mi>C</mi><mn>3</mn></msup></semantics></math></inline-formula>-Sex, a smart chatbot that uses Natural Language Processing (NLP) to interact with suspects in order to profile their interest regarding online child sexual abuse. This solution is based on our Artificial Conversational Entity (ACE) that connects to different online chat services to start a conversation. The ACE is designed using generative and rule-based models in charge of generating the posts and replies that constitute the conversation from the chatbot side. The proposed solution also includes a module to analyze the conversations performed by the chatbot and calculate a set of 25 features that describes the suspect’s behavior. After 50 days of experiments, the chatbot generated a dataset with 7199 profiling vectors with the features associated to each suspect. Afterward, we applied an unsupervised method to describe the results that differentiate three groups, which we categorize as indifferent, interested, and pervert. Exhaustive analysis is conducted to validate the applicability and advantages of our solution. |
topic |
chatbot online child sexual abuse criminal profiling natural language processing law enforcement agencies |
url |
https://www.mdpi.com/2079-9292/9/11/1779 |
work_keys_str_mv |
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