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Campo DC | Valor | Lengua/Idioma |
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dc.contributor.author | Martínez, Rodrigo | - |
dc.date.accessioned | 2021-09-01T12:35:12Z | - |
dc.date.available | 2021-09-01T12:35:12Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Martínez, R. Enhancing web application attack detection using machine learning [Preprint]. Publicado en : LADC 2018, 8th Latin-American Symposium on Dependable Computing, Foz de Iguaçu, Brazil, 8-10 October 2018. | es |
dc.identifier.uri | https://hdl.handle.net/20.500.12008/29285 | - |
dc.description | LADC 2018, 8th Latin-American Symposium on Dependable Computing, Foz de Iguaçu, Brazil, 8-10 October 2018. | es |
dc.description.abstract | The exploit of vulnerabilities present in Web applications has been the main attack vector in the last decade biggest data breaches. In this work we put forward a framework to leverage the performance of Web Application Firewalls (WAFs) using machine learning techniques. We propose the use of two types of machine learning models: a multi-class approach for the scenario when valid and attack data is available and alternatively a one-class model when only valid data is at hand. The use of both models to predict potential malicious traffic has shown to outperform MODSECURITY, a widely deployed WAF technology, configured with the OWASP Core Rule Set out of the box. We also present a prototype that integrates the one-class model with MODSECURITY. | es |
dc.format.extent | 4 p. | es |
dc.format.mimetype | application/pdf | es |
dc.language.iso | en | es |
dc.rights | Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014) | es |
dc.subject | Web Application Firewall | es |
dc.subject | Web Application Security | es |
dc.subject | Machine Learning | es |
dc.subject | Pattern Recognition | es |
dc.title | Enhancing web application attack detection using machine learning | es |
dc.type | Preprint | es |
dc.contributor.filiacion | Martínez Rodrigo, Universidad de la República (Uruguay). Facultad de Ingeniería. | - |
dc.rights.licence | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) | es |
Aparece en las colecciones: | Reportes Técnicos - Instituto de Computación |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | ||
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MAR18.pdf | Preprint | 513,99 kB | Adobe PDF | Visualizar/Abrir |
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