Resumo

SALAS CONDE, Julio Jesús; MARTIN ORTIZ, Manuel  e  CARNEIRO DIAZ, Víctor Manuel. Methodology for Identification and Classifying of Cybercrime on Tor Network through the Use of Cryptocurrencies Based on Web Textual Contents. Comp. y Sist. [online]. 2022, vol.26, n.1, pp.347-356.  Epub 08-Ago-2022. ISSN 2007-9737.  https://doi.org/10.13053/cys-26-1-4178.

The Fourth Industrial Revolution has propelled global society into a new era of information and knowledge, transforming the economy and society of many countries. The global digitization process impacts more than half of the world population with internet access and the increase in the incidence of crimes in cyberspace, affecting the population mainly online fraud, crimes that attack vulnerable groups such as girls, boys and adolescents, as well as the diversity of cyberattacks with an impact on the availability, integrity and confidentiality of essential data and information systems of public, private and academic institutions. Most of these antisocial behaviors are published on the Deep Internet due to its anonymity, one of these being the TOR browser project (The Onion Router), in order to address this problem, a methodology was developed that allows the authorities in Mexico have a database that allows correlating data published on this network with the investigations they carry out derived from reports of cybercrimes to obtain lines of investigation based on the identification and classification of cybercrime, and using language engineering techniques and of knowledge as the methods of creation of ontologies of Ding, Y; Foo, S; recovery tool for large information files on websites such as wget, security measures for browsing the Deep Internet such as "Whonix Gateway", "Text Cleaning" techniques, extraction and classification features such as "Jaccard and Cosine Similarity Calculation", among other.

Palavras-chave : Cybercrime; cryptocurrencies; fraud identification; web textual contents; detection tools.

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