Deep Reinforcement Learning for Attacking Wireless Sensor Networks

Recent advances in Deep Reinforcement Learning allow solving increasingly complex problems. In this work, we show how current defense mechanisms in Wireless Sensor Networks are vulnerable to attacks that use these advances. We use a Deep Reinforcement Learning attacker architecture that allows havin...

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Detalles Bibliográficos
Autores principales: Parras, Juan, Hüttenrauch, Maximilian, Zazo, Santiago, Neumann, Gerhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8231574/
https://www.ncbi.nlm.nih.gov/pubmed/34204726
http://dx.doi.org/10.3390/s21124060

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8231574/
https://www.ncbi.nlm.nih.gov/pubmed/34204726
http://dx.doi.org/10.3390/s21124060

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