27 citations · 76 across the 20 of their papers we have counts for
9 papers · 1 filter
DecoyTrace: Toxic Decoys for Active Defense in Decentralized Federated Learning
Pedro Beltrán-López, Enrique Tomás Martínez Beltrán, Pantaleone Nespoli +2
Decentralized Federated Learning (DFL) eliminates the central aggregation server, reducing the single point of observation that traditional defenses against attacks rely on. As a r…
Neural cyberattacks applied to the vision under realistic visual stimuli
Victoria Magdalena López Madejska, Sergio López Bernal, Gregorio Martínez Pérez +1
Brain-Computer Interfaces (BCIs) are systems traditionally used in medicine and designed to interact with the brain to record or stimulate neurons. Despite their benefits, the lite…
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…
Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification
Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Gérôme Bovet +1
In the last years, the number of IoT devices deployed has suffered an undoubted explosion, reaching the scale of billions. However, some new cybersecurity issues have appeared toge…
Trust-as-a-Service: A reputation-enabled trust framework for 5G networks
José María Jorquera Valero, Pedro Miguel Sánchez Sánchez, Manuel Gil Pérez +2
Trust, security, and privacy are three of the major pillars to assemble the fifth generation network and beyond. Despite such pillars are principally interconnected, they arise a m…
Eight Reasons Why Cybersecurity on Novel Generations of Brain-Computer Interfaces Must Be Prioritized
Sergio López Bernal, Alberto Huertas Celdrán, Gregorio Martínez Pérez
This article presents eight neural cyberattacks affecting spontaneous neural activity, inspired by well-known cyberattacks from the computer science domain: Neural Flooding, Neural…
Neuronal Jamming Cyberattack over Invasive BCI Affecting the Resolution of Tasks Requiring Visual Capabilities
Sergio López Bernal, Alberto Huertas Celdrán, Gregorio Martínez Pérez
Invasive Brain-Computer Interfaces (BCI) are extensively used in medical application scenarios to record, stimulate, or inhibit neural activity with different purposes. An example…
Federated Learning for Malware Detection in IoT Devices
Valerian Rey, Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán +2
This work investigates the possibilities enabled by federated learning concerning IoT malware detection and studies security issues inherent to this new learning paradigm. In this…
AuthCODE: A Privacy-preserving and Multi-device Continuous Authentication Architecture based on Machine and Deep Learning
Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Lorenzo Fernández Maimó +1
The authentication field is evolving towards mechanisms able to keep users continuously authenticated without the necessity of remembering or possessing authentication credentials.…