Ítem
Acceso Abierto
FCTNLP: Fighting cyberterrorism with natural language processing
| dc.contributor.advisor | Díaz López, Daniel Orlando | |
| dc.creator | Zapata Rozo, Andrés Felipe | |
| dc.creator.degree | Profesional en Matemáticas Aplicadas y Ciencias de la Computación | es |
| dc.creator.degreeLevel | Pregrado | |
| dc.creator.degreetype | Full time | es |
| dc.date.accessioned | 2022-08-22T19:11:40Z | |
| dc.date.available | 2022-08-22T19:11:40Z | |
| dc.date.created | 2021-11-26 | |
| dc.description | Las redes sociales son una rica fuente de datos y han sido utilizadas para promover u organizar ciberdelitos que afectan al mundo real. Por ello, las fuerzas del orden se interesan por la información crucial que puede obtenerse de estas fuentes. La cantidad de información y el lenguaje informal que se utiliza para difundir la información hace que el Procesamiento del Lenguaje Natural (PLN) sea una excelente herramienta para realizar análisis sobre las publicaciones en las redes sociales. Por ello, en esta propuesta se integra una arquitectura con tres modelos de PLN para proporcionar un análisis exhaustivo de fuentes abiertas como los medios sociales. Este análisis extrae entidades del texto, identifica clusters de usuarios y su respectiva polaridad, finalmente todos los resultados se relacionan en una base de datos gráfica. Esta arquitectura se puso a prueba utilizando datos de un escenario real para determinar su viabilidad. | es |
| dc.description.abstract | The social networks are a rich source of data and have been used to promote or organize cybercrimes that affect the real world. Because of this, the law enforcement agency are interest in the crucial information that can be get on this sources. The amount of information and the informal language which is used to spread information makes the Natural Language Processing (NLP) and excellent tool to make analysis over post in social media. That is why, in this proposal an architecture with three NLP models are integrated to provide an exhaustive analysis from open sources like social media. This analysis extract entities from the text, identifies clusters of users and their respective polarity, finally all of the results are related in a graph database. This architecture was under test using data from a real scenario in order to determine their feasibility. | es |
| dc.format.extent | 26 pp | es |
| dc.format.mimetype | application/pdf | es |
| dc.identifier.doi | https://doi.org/10.48713/10336_34736 | |
| dc.identifier.uri | https://repository.urosario.edu.co/handle/10336/34736 | |
| dc.language.iso | eng | es |
| dc.publisher | Universidad del Rosario | |
| dc.publisher.department | Escuela de Ingeniería, Ciencia y Tecnología | |
| dc.publisher.program | Programa de Matemáticas Aplicadas y Ciencias de la Computación - MACC | |
| dc.rights.accesRights | info:eu-repo/semantics/openAccess | es |
| dc.rights.acceso | Abierto (Texto Completo) | es |
| dc.source.bibliographicCitation | Council of Europe. Explanatory Report to the Convention on Cybercrime. https://rm.coe.int/CoERMPublicCommonSearc hServices/DisplayDCTMContent?documentId=09000016800c ce5b. 2001. | es |
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| dc.source.bibliographicCitation | Iv´an Castillo-Z´u˜niga et al. “Internet Data Analysis Methodology for Cyberterrorism Vocabulary Detection, Combining Techniques of Big Data Analytics, NLP and Semantic Web”. In: International Journal on Semantic Web and Information Systems 16 (Jan. 2020), pp. 69–86. doi: 10.4018/IJSWIS.20 20010104. | es |
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| dc.source.bibliographicCitation | V. N. Uzel, E. Sara¸c E¸ssiz, and S. Ay¸se Ozel. “Using Fuzzy ¨ Sets for Detecting Cyber Terrorism and Extremism in the Text”. In: 2018 Innovations in Intelligent Systems and Applications Conference (ASYU). 2018, pp. 1–4. doi: 10.1109 /ASYU.2018.8554017. | es |
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| dc.source.instname | instname:Universidad del Rosario | |
| dc.source.reponame | reponame:Repositorio Institucional EdocUR | |
| dc.subject | OSINT | es |
| dc.subject | NER | es |
| dc.subject | Ciberterrorismo | es |
| dc.subject | Procesamiento de Lenguaje Natural | es |
| dc.subject | Similitud semántica | es |
| dc.subject | Análisis de sentimientos | es |
| dc.subject.ddc | Matemáticas | es |
| dc.subject.keyword | Cyberterrorism | es |
| dc.subject.keyword | OSINT | es |
| dc.subject.keyword | NLP | es |
| dc.subject.keyword | NER | es |
| dc.subject.keyword | Natural Language Processing | es |
| dc.subject.keyword | Sentiment Analysis | es |
| dc.subject.keyword | Semantic Similarity | es |
| dc.title | FCTNLP: Fighting cyberterrorism with natural language processing | es |
| dc.title.TranslatedTitle | FCTNLP: Luchando contra el ciberterrorismo con procesamiento de lenguaje natural | es |
| dc.type | bachelorThesis | es |
| dc.type.document | Trabajo de grado | es |
| dc.type.hasVersion | info:eu-repo/semantics/acceptedVersion | |
| dc.type.spa | Trabajo de grado | es |
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