Empowering DDoS Attack Prediction through Machine Learning and Deep Learning
IEEE Communications Society , la Maestría en Seguridad de la Información de DISCuniandes y Universidad de los Andes - Colombia , la Rama Estudiantil IEEE UniAndes, y los capítulos estudiantiles de Comunicaciones y Computación tienen el gusto de invitarlos a la charla Empowering DDoS Attack Prediction through Machine Learning and Deep Learning impartida por la Ph.D. Michele Nogueira .
Date and Time
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Registration
- Date: 21 Nov 2023
- Time: 06:00 PM to 07:00 PM
- All times are (UTC-05:00) Bogota
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- Co-sponsored by Uiversidad de Los Andes
Speakers
Michele Nogueira of UFMG
Empowering DDoS Attack Prediction through Machine Learning and Deep Learning
Biography:
Michele Nogueira is an Associate Professor in the Computer Science Department at Federal University of Minas Gerais (UFMG), Brazil. She received her doctorate in Computer Science from the University Pierre et Marie Curie – Sorbonne Université, France. She was on a sabbatical leave at Carnegie Mellon University, USA (2016-2017). Her research interests include wireless networks, network security and dependability. She has worked on providing resilience to self-organized, cognitive and wireless networks by adaptive and opportunistic approaches. Today, her research focuses on creating network security intelligence supported by data science. Dr. Nogueira was one of the pioneers in addressing survivability issues in self-organized wireless networks, being the work “A Survey of Survivability in Mobile Ad Hoc Networks”, one of her prominent scientific contributions. She has been a recipient of Academic Scholarships from Brazilian Government in her undergraduate and graduate years, and of international grants such as from the ACM SIGCOMM Geodiversity program. She served as Associate Technical Editor for the IEEE Communications Magazine. She served as chair for the IEEE ComSoc Internet Technical Committee. She is an ACM and IEEE Senior Member.
Email:
Address:Belo Horizonte, Brazil
Media
| Baner Nogueira - DL | 441.29 KiB |