Seguridad basada en patrones de tráfico para las redes de comunicaciones utilizadas en infraestructura critica

dc.contributorForero Rodríguez, Felipe
dc.contributorPeña Traslaviña, Néstor Misael
dc.creatorArias Recio, Felipe
dc.date.accessioned2023-08-09T15:39:42Z
dc.date.accessioned2023-09-06T23:13:42Z
dc.date.available2023-08-09T15:39:42Z
dc.date.available2023-09-06T23:13:42Z
dc.date.created2023-08-09T15:39:42Z
dc.date.issued2023-06-27
dc.identifierhttp://hdl.handle.net/1992/69489
dc.identifierinstname:Universidad de los Andes
dc.identifierreponame:Repositorio Institucional Séneca
dc.identifierrepourl:https://repositorio.uniandes.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8726325
dc.description.abstractEn este proyecto de investigación se busca replicar los esquemas de ciberseguridad que dependen de los patrones de tráfico de una red de comunicaciones, obteniendo resultados comparables con el documento "Anomaly Traffic Detection with Verifiable Interpretation in Industrial Networks".
dc.languagespa
dc.publisherUniversidad de los Andes
dc.publisherIngeniería Electrónica
dc.publisherFacultad de Ingeniería
dc.publisherDepartamento de Ingeniería Eléctrica y Electrónica
dc.relationESED Cyber Security & IT Solutions, "ESED Cyber Security & IT Solutions," [Online]. Available: https://www.esedsl.com/blog/primer-ciberataque-historia-y-ciberataques-que- han- perdurado-tiempo.
dc.relationU.S. Bureau of Statistics, "U.S. Bureau of Statistics," [Online]. Available: https://www.bls.gov/ooh/computer-and-information-technology/information-security- analysts.htm#tab-6
dc.relationPortafolio, "Portafolio," Diciembre 2022. [Online]. https://www.portafolio.co/negocios/empresas/eps-sanitas-detalles-del-ciberataque-que- sufrio-grupo-keralty-575968.
dc.relationH. Zhu, J. Tian, Z. Tian, S. Zhu, H. Li and Y. Zhang, "Anomaly Traffic Detection with Verifiable Interpretation in Industrial Networks," IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress, 2021.
dc.relationX. Zu, Z. Fnag, L. Qi, X. Zhang, Q. He and X. Zhou, "TripRes: Traffic Flow Prediction Driven Resource Reservation for Multimedia IoV with Edge Computing," ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 17, no. 2, pp. 1-21, 21 Abril 2021.
dc.relationA. L. Buczak and E. Guven, "A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection," IEEE Communications Surveys & Tutorials, vol. 18, no. 2, pp. 1153-1176, 2016.
dc.relationS. Torabi, A. Boukhtouta, C. Assi and M. Dabbabi, "Detecting Internet Abuse by Analyzing Passive DNS Traffic: A Survey of Implemented Systems," IEEE Communications Surveys & Tutorials, vol. 20, no. 4, pp. 3389-3415, 2018
dc.relationU. Dixit, S. Bhatia and P. Bhatia, "A Review of Supervised Machine Learning Algorithms," International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COM-IT-CON), 26-27 May 2022.
dc.relationM. L. Alzáte and N. S. Londoño, "Machine Learning y Seguridad: Detección de Correos Falsos y Detección de Intrusos," Universidad de los Andes, Bogota, 2020.
dc.relationD. A. Torres, "Sistemas de Deteccion de Intrusos Basados en Redes Neuronales Artificiales en Ambientes con Adversarios," Universidad de los Andes, Bogota, 2019
dc.relationK. Wu and Z. Chen, "A Novel Intrusion Detection Model for a Massive Network Using Convolutional Neural Networks," IEEE Access, vol. 6, pp. 50850-50859, September 2018.
dc.relationN. Tavallae, E. Bagheri, W. Lu and A. Ghorbani, "A Detailed Analysis of the KDD CUP 99 Data Set," Submitted to Second IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA), 2009
dc.relationJ. E. Hernandez, "Implementación de IDS con Machine Learning en redes IoT con dispositivo de Edge computing," Universidad de los Andes, Bogota, 2022.
dc.relationR. A. Calix, "Machine Learning for Cyber Security Professionals," in Getting started with deep learning: programming and methodologies using python, Hammond, IN: Purdue University, 2017.
dc.rightsAtribución 4.0 Internacional
dc.rightshttp://creativecommons.org/licenses/by/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.titleSeguridad basada en patrones de tráfico para las redes de comunicaciones utilizadas en infraestructura critica
dc.typeTrabajo de grado - Pregrado


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