no code implementations • 11 Aug 2023 • Chao Feng, Alberto Huertas Celdran, Pedro Miguel Sanchez Sanchez, Jan Kreischer, Jan von der Assen, Gerome Bovet, Gregorio Martinez Perez, Burkhard Stiller
Recent research has shown that the integration of Reinforcement Learning (RL) with Moving Target Defense (MTD) can enhance cybersecurity in Internet-of-Things (IoT) devices.
no code implementations • 20 Jul 2023 • Muriel Figueredo Franco, Fabian Künzler, Jan von der Assen, Chao Feng, Burkhard Stiller
Therefore, managing risk exposure and cybersecurity strategies is essential for digitized companies that want to survive in competitive markets.
no code implementations • 27 Jun 2023 • Jan von der Assen, Alberto Huertas Celdrán, Janik Luechinger, Pedro Miguel Sánchez Sánchez, Gérôme Bovet, Gregorio Martínez Pérez, Burkhard Stiller
Cybersecurity solutions have shown promising performance when detecting ransomware samples that use fixed algorithms and encryption rates.
1 code implementation • 30 Dec 2022 • Alberto Huertas Celdrán, Pedro Miguel Sánchez Sánchez, Jan von der Assen, Timo Schenk, Gérôme Bovet, Gregorio Martínez Pérez, Burkhard Stiller
Reinforcement Learning (RL) could be an effective approach to optimize the MTD selection through trial and error, but the literature fails when i) evaluating the performance of RL and MTD solutions in real-world scenarios, ii) studying whether behavioral fingerprinting is suitable for representing SBC's states, and iii) calculating the consumption of resources in SBC.
no code implementations • 14 Oct 2022 • Jan von der Assen, Alberto Huertas Celdrán, Pedro Miguel Sánchez Sánchez, Jordan Cedeño, Gérôme Bovet, Gregorio Martínez Pérez, Burkhard Stiller
Malware affecting Internet of Things (IoT) devices is rapidly growing due to the relevance of this paradigm in real-world scenarios.