17 citations · 26 across the 4 of their papers we have counts for
9 papers · 1 filter
CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation
Chao Feng, Alberto Huertas Celdran, Pedro Miguel Sanchez Sanchez +5
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. Nevert…
RCVaR: an Economic Approach to Estimate Cyberattacks Costs using Data from Industry Reports
Muriel Figueredo Franco, Fabian Künzler, Jan von der Assen +2
Digitization increases business opportunities and the risk of companies being victims of devastating cyberattacks. Therefore, managing risk exposure and cybersecurity strategies is…
RansomAI: AI-powered Ransomware for Stealthy Encryption
Jan von der Assen, Alberto Huertas Celdrán, Janik Luechinger +4
Cybersecurity solutions have shown promising performance when detecting ransomware samples that use fixed algorithms and encryption rates. However, due to the current explosion of…
MTFS: a Moving Target Defense-Enabled File System for Malware Mitigation
Jan von der Assen, Alberto Huertas Celdrán, Rinor Sefa +2
Ransomware has remained one of the most notorious threats in the cybersecurity field. Moving Target Defense (MTD) has been proposed as a novel paradigm for proactive defense. Altho…
SECAdvisor: a Tool for Cybersecurity Planning using Economic Models
Muriel Figueredo Franco, Christian Omlin, Oliver Kamer +2
Cybersecurity planning is challenging for digitized companies that want adequate protection without overspending money. Currently, the lack of investments and perverse economic inc…
FederatedTrust: A Solution for Trustworthy Federated Learning
Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Ning Xie +3
The rapid expansion of the Internet of Things (IoT) and Edge Computing has presented challenges for centralized Machine and Deep Learning (ML/DL) methods due to the presence of dis…