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Enrique Tomás Martínez Beltrán
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Enrique Tomás Martínez Beltrán

Ph.D. student at the University of Murcia working at the intersection of federated learning, cybersecurity, and privacy-preserving AI for real-world systems.

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  3. SecBrain: A Framework to Detect Cyberattacks Revealing Sensitive Data in Brain-Computer Interfaces
Book chapter2022

Advances in Malware and Data-Driven Network Security

SecBrain: A Framework to Detect Cyberattacks Revealing Sensitive Data in Brain-Computer Interfaces

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Quick facts

Year
2022
Venue
Advances in Malware and Data-Driven Network Security
Identifier
martinezbeltran2022secbrain

Suggested citation

Enrique Tomás Martínez Beltrán, Mario Quiles Pérez, Sergio López Bernal, Alberto Huertas Celdrán, Gregorio Martínez Pérez (2022). SecBrain: A Framework to Detect Cyberattacks Revealing Sensitive Data in Brain-Computer Interfaces. Advances in Malware and Data-Driven Network Security.

Abstract

Authors

Enrique Tomás Martínez BeltránMario Quiles PérezSergio López BernalAlberto Huertas CeldránGregorio Martínez Pérez

Keywords

Related publications

Works with stronger overlap in topic, type, and tags.

Conference paper2022

VII Jornadas Nacionales de Investigación en Ciberseguridad (JNIC 2022)

A Review of Noise-based Cyberattacks Generating Fake P300 Waves in Brain-Computer Interfaces

Enrique Tomás Martínez Beltrán, Mario Quiles Pérez, Sergio López Bernal, Alberto Huertas Celdrán, Gregorio Martínez Pérez

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Journal article2022

Cluster Computing

Noise-based cyberattacks generating fake P300 waves in brain--computer interfaces

Enrique Tomás Martínez Beltrán, Mario Quiles Pérez, Sergio López Bernal, Alberto Huertas Celdrán, Gregorio Martínez Pérez

Most of the current Brain--Computer Interfaces (BCIs) application scenarios use electroencephalographic signals (EEG) containing the subject's information. It means that if EEG were maliciously manipulated, the proper fu...

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Journal article2022

Expert Systems with Applications

SAFECAR: A Brain–Computer Interface and intelligent framework to detect drivers’ distractions

Enrique Tomás Martínez Beltrán, Mario Quiles Pérez, Sergio López Bernal, Gregorio Martínez Pérez, Alberto Huertas Celdrán

As recently reported by the World Health Organization (WHO), the high use of intelligent devices such as smartphones, multimedia systems, or billboards causes an increase in distraction and, consequently, fatal accidents...

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Related Research

DEFENDIS: Decentralized Federated Learning for IoT Device Identification and Security

Apr 2023 — Nov 2023

DEFENDIS: Decentralized Federated Learning for IoT Device Identification and Security

DEFENDIS develops a framework for uniquely identifying IoT devices in a distributed manner while solving security threats through decentralized federated learning.

EU-GUARDIAN: European Framework and Proofs-of-concept for the Intelligent Automation of Cyber Defence Incident Management

Dec 2022 — Nov 2025

EU-GUARDIAN: European Framework and Proofs-of-concept for the Intelligent Automation of Cyber Defence Incident Management

A cutting-edge AI-based solution for automating cyber defence incident management processes, enhancing EU cyber defence posture and operational capabilities.