Open source intelligence (OSINT) as support of cybersecurity operations. Use of OSINT in a colombian context and sentiment Analysis

Open source intelligence (OSINT) is used to obtain and analyze information related to adversaries, so it can support risk assessments aimed to prevent damages against critical assets. This paper presents a research about different OSINT technologies and how these can be used to perform cyber intelli...

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Autores:
Hernandez Mediná, Martin Jose
Pinzón Hernández, Cristian Camilo
Díaz López, Daniel Orlando
Garcia Ruiz, Juan Carlos
Pinto Rico, Ricardo Andrés
Tipo de recurso:
Article of investigation
Fecha de publicación:
2018
Institución:
Escuela Colombiana de Ingeniería Julio Garavito
Repositorio:
Repositorio Institucional ECI
Idioma:
eng
OAI Identifier:
oai:repositorio.escuelaing.edu.co:001/1459
Acceso en línea:
https://repositorio.escuelaing.edu.co/handle/001/1459
https://doi.org/10.14483/2322939X.13504
https://revistas.udistrital.edu.co/index.php/vinculos/article/view/13504
Palabra clave:
OSINT
Ciberinteligencia (seguridad informática)
Seguridad informática
Cyberintelligence
Open source intelligence
Adversary profiling
Machine learning
Sentiment analysis
Data science
Análisis de sentimientos
Aprendizaje automático
Ciber inteligencia
Ciencia de datos
Inteligencia de fuentes abiertas
Perfilamiento de adversarios
Rights
openAccess
License
https://creativecommons.org/licenses/by/4.0/
Description
Summary:Open source intelligence (OSINT) is used to obtain and analyze information related to adversaries, so it can support risk assessments aimed to prevent damages against critical assets. This paper presents a research about different OSINT technologies and how these can be used to perform cyber intelligence tasks. One of the key components in the operation of OSINT tools are the “transforms”, which are used to establish relations between entities of information from queries to different open sources. A set of transforms addressed to the Colombian context are presented, which were implemented and contributed to the community allowing to the law enforcement agencies to develop information gathering process from Colombian open sources. Additionally, this paper shows the implementation of three machine learning models used to perform sentiment analysis over the information obtained from an adversary. Sentiment analysis can be extremely useful to understand the motivation that an adversary can have and, in this way, define proper cyber defense strategies. Finally, some challenges related to the application of OSINT techniques are identified and described.