Machine Learning applicated in cybersecurity
DOI:
https://doi.org/10.71112/4mvx1985Keywords:
machine learning, cybersecurity, computer security, intrusion detection, internet of thingsAbstract
Machine Learning (ML) has become one of the most widely used technologies and tools today; however, its utility and significance are often overlooked. The purpose of this research is to examine how ML is currently being applied in the field of cybersecurity through a comprehensive literature review. This analysis highlights the various applications of ML in data security mechanisms, information systems, and multiple domains related to information security. The findings demonstrate that ML plays a critical role in security mechanisms for Internet of Things (IoT) devices, Intrusion Detection Systems (IDS), website analysis, banking fraud detection, and Industry 4.0—essentially permeating nearly every technology we use.
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Anthi, E., Williams, L., Rhode, M., Burnap, P., & Wedgbury, A. (2021). Adversarial attacks on machine learning cybersecurity defences in Industrial Control Systems. Journal of Information Security and Applications, 58. https://doi.org/10.1016/j.jisa.2020.102717
Cando, M., & Medina, P. (2021). Prevención en ciberseguridad: enfocada a los procesos de infraestructura tecnológica. 3C TIC: Cuadernos de Desarrollo Aplicados a Las TIC, 10(1), 17–41. https://doi.org/10.17993/3ctic.2021.101.17-41
Dasgupta, D., Akhtar, Z., & Sen, S. (2020). Machine learning in cybersecurity: a comprehensive survey. Journal of Defense Modeling and Simulation. https://doi.org/10.1177/1548512920951275
Dueñas, J. (2020). Aplicación de técnicas de machine learning a la ciberseguridad: Aprendizaje supervisado para la detección de amenazas web mediante clasificación basada en árboles de decisión. https://openaccess.uoc.edu/items/f49ea127-88ab-47b9-96a4-53194b502e96#page=1
Duzhin, F., & Gustafsson, A. (2018). Machine learning-based app for self-evaluation of teacher-specific instructional style and tools. Education Sciences, 8(1). https://doi.org/10.3390/educsci8010007
Fernández, A. (2019). Machine Learning en Ciberseguridad. https://openaccess.uoc.edu/server/api/core/bitstreams/957679da-ab99-4016-b962-225e8823445f/content
Flores, C. (2020). Inteligencia Artificial, Machine Learning, Deep Learning aplicados a la Ciberseguridad. https://ojs.umsa.bo/index.php/inf_fcpn_pgi/article/view/96
Forero, W., & Bennasar, F. (2024). Técnicas y aplicaciones del Machine Learning e Inteligencia Artificial en educación: una revisión sistemática. RIED-Revista Iberoamericana de Educacion a Distancia, 27(1), 209–253. https://doi.org/10.5944/ried.27.1.37491
Gómez, E., Fernando, D., Aponte, G., & Betancourt, L. (2014). Literature review methodology for scientific and information management, through its structuring and systematization Metodología para la revisión bibliográfica y la gestión de información de temas científicos, a través de su estructuración y sistematización. DYNA, 81(184), 158–163. http://dyna.medellin.unal.edu.co/
Haider, A., Adnan, M., Rehman, A., Ur, M., & Seok Hyung. (2020). A real-time sequential deep extreme learning machine cybersecurity intrusion detection system. Computers, Materials and Continua, 66(2), 1785–1798. https://doi.org/10.32604/cmc.2020.013910
Lopez, M., Lombardo, J., López, M., Alba, C., Velasco, S., Braojos, M. A., & Fuentes-García, M. (2020). Intelligent Detection and Recovery from Cyberattacks for Small and Medium-Sized Enterprises. International Journal of Interactive Multimedia and Artificial Intelligence, 6(3), 55. https://doi.org/10.9781/ijimai.2020.08.003
Martínez, J., Iglesias, C., & García, P. J. (2019). Review: machine learning techniques applied to cybersecurity. International Journal of Machine Learning and Cybernetics, 10(10), 2823–2836. https://doi.org/10.1007/s13042-018-00906-1
Navarro, A., Urcuqui, C., García, M., & Osorio, J. L. (2018). Ciberseguridad: un enfoque desde la ciencia de datos. Universidad Icesi. https://doi.org/10.18046/EUI/ee.4.2018
Pérez, M., Rial, G., Sotelo, R., & Gurméndez, M. (2020). Clasificador de logs de acceso para detección de incidentes de ciberseguridad. Memoria Investigaciones En Ingeniería, 18. https://doi.org/10.36561/ing.18.7
Pinto, R., Hernández, M., Pinzón, C., Díaz, D., & García, J. (2018). Open source intelligence (OSINT) in a colombian context and sentiment analysis. Revista Vínculos, 15(2), 195–214. https://doi.org/10.14483/2322939x.13504
Ramírez, D., Garcés, L., Doria, T., Franco, S., Valencia, A., Rodríguez, P., & Espinoza, J. (2023). Tendencias investigativas en el uso de Machine Learning en la ciberseguridad. Iberian Journal of Information Systems and Technologies. https://www.proquest.com/openview/c9bf3f3b2192c011f0620adce0649ab3/1?pq-origsite=gscholar&cbl=1006393
Rozo Florelva. (2020). Revisión de las tecnologías presentes en la industria 4.0. Revista UIS Ingenierías, 19(2), 177–191. https://doi.org/10.18273/revuin.v19n2-2020019
Vilone, G., & Longo, L. (2021). Classification of Explainable Artificial Intelligence Methods through Their Output Formats. Machine Learning and Knowledge Extraction, 3(3), 615–661. https://doi.org/10.3390/make3030032
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