| Metadato | Etiqueta | Valor | Idioma |
|---|---|---|---|
| dc.contributor.author | Autor | Rodríguez, Marcelo | - |
| dc.contributor.author | Autor | Betarte, Gustavo | - |
| dc.contributor.author | Autor | Calegari, Daniel | - |
| dc.contributor.filiacion | Filiación | Rodríguez Marcelo, Universidad de la República (Uruguay). Facultad de Ingeniería. | - |
| dc.contributor.filiacion | Filiación | Betarte Gustavo, Universidad de la República (Uruguay). Facultad de Ingeniería | - |
| dc.contributor.filiacion | Filiación | Calegari Daniel, Universidad de la República (Uruguay). Facultad de Ingeniería. | - |
| dc.date.accessioned | Fecha ingreso | 2021-09-01T12:32:53Z | - |
| dc.date.available | Fecha disponible | 2021-09-01T12:32:53Z | - |
| dc.date.issued | Año de publicación | 2021 | - |
| dc.description | Descripción | IEEE URUCON 2021, Montevideo, Uruguay. 24-26 November, 2021. | es |
| dc.description.abstract | Resumen | Reacting adequately to cybersecurity attacks requires observing the attackers’ knowledge, skills, and behaviors to examine their influence over the system and understand the characteristics associated with these attacks. Profiling an attacker allows generating security countermeasures that can be adopted even from the design of the systems. For automated attackers, e.g. malware, it is possible to identify some structured behavior, i.e. a process-like behavior consisting of several (partial) ordered activities. Process Mining (PM) is a discipline from the organizational context that focuses on analyzing the event logs associated with executing the system’s processes to discover many aspects of process behavior. Few proposals are applying PM to attacker profiling. In this work, we explore the use of PM techniques to identify the behavior of cyber attackers. In particular, we illustrate, using an application example, how they can be adapted to an environment dominated by automated attackers. We discuss preliminary results and provide guidelines for future work. | es |
| dc.format.extent | Extensión | 4 p. | es |
| dc.format.mimetype | Formato | application/pdf | es |
| dc.identifier.citation | Citación | Rodríguez, M., Betarte, G. y Calegari, D. A Process Mining-based approach for Attacker Profiling [Preprint]. Publicado en : IEEE URUCON 2021, Montevideo, Uruguay. 24-26 November, 2021. | es |
| dc.identifier.uri | URI | https://hdl.handle.net/20.500.12008/29279 | - |
| dc.language.iso | Idioma | en | es |
| dc.rights | Derechos | 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.rights.licence | Licencia | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) | es |
| dc.subject | Palabras clave | Cybersecurity | es |
| dc.subject | Palabras clave | Process mining | es |
| dc.subject | Palabras clave | Behaviour | es |
| dc.subject | Palabras clave | Malware | es |
| dc.title | Título | A Process Mining-based approach for Attacker Profiling | es |
| dc.type | Tipo de documento | Preprint | es |
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| RBC21.pdf | Preprint | 327.38 KB | Adobe PDF |