Machine Learning for Cyber Security: Mitigating Cyber Attacks and Detecting Malicious Activities in Network Traffic
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Asmaa Nassar [1]
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[1] Universidad de Almería
Universidad de Almería
Almería, España
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- Localización: VI Jornadas de Doctorado en Informática: 10 de Febrero 2023. Universidad de Almería / coord. por Luis Fernando Iribarne Martínez, Ester Martín Garzón, Manuel Berenguel Soria, 2023, ISBN 978-84-1351-224-2, págs. 5-13
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
With the widespread use of Internet networks and the remarkable digital transformationwith mobile devices, cloud servers, social media, and the Internet of Things (IoT), cybersecurity issueshave become among the most important issues and challenge to face, and diligence in finding solutionsto ensure the safety of networks, devices, and data transmitted in network traffic. In this thesis, we willuse machine learning (ML) techniques to devise a methodology for detecting malicious activities. Wewill use a specific database and mixed analysis method that will help to collect numerical and nonnumericaldata for investigating the research question. In addition to that, the mixed analysis willsupport and improve the analysis of graphs and tables.
