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Enrique Tomás Martínez Beltrán

Federated learning, trustworthy AI and cyberdefense research, focused on systems that are robust, privacy-preserving and useful in security operations.

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  2. Publications on Federated Learning, AI and Cybersecurity
  3. Stealth Spectrum Sensing Data Falsification Attacks Affecting IoT Spectrum Monitors on the Battlefield
Conference paper2023

MILCOM 2023 - 2023 IEEE Military Communications Conference (MILCOM)

Stealth Spectrum Sensing Data Falsification Attacks Affecting IoT Spectrum Monitors on the Battlefield

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Military communicationFile systemsMachine learningFingerprint recognitionSensor systemsInternetBehavioral sciencesSpectrum Sensing Data Falsification AttacksBattlefieldSpectrum MonitoringFingerprintingSystem calls

Abstract

Authors

Pedro Miguel Sánchez SánchezEnrique Tomás Martínez BeltránAlberto Huertas CeldránRobin WassinkGérôme BovetGregorio Martínez PérezBurkhard Stiller

Keywords

Military communicationFile systemsMachine learningFingerprint recognitionSensor systemsInternetBehavioral sciencesSpectrum Sensing Data Falsification AttacksBattlefieldSpectrum MonitoringFingerprintingSystem calls

Related publications

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

Conference paper2023

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence

Fedstellar: a platform for training models in a privacy-preserving and decentralized fashion

Enrique Tomás Martínez Beltrán, Pedro Miguel Sánchez Sánchez, Sergio López Bernal, Gérôme Bovet, Manuel Gil Pérez, Gregorio Martínez Pérez, Alberto Huertas Celdrán

This paper presents Fedstellar, a platform for training decentralized Federated Learning (FL) models in heterogeneous topologies in terms of the number of federation participants and their connections. Fedstellar allows...

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Journal article2025

IEEE Communications Magazine

Flighter: Decentralized Federated Learning and Situational Awareness for Secure Military Aerial Reconnaissance

Enrique Tomás Martínez Beltrán, Pedro Miguel Sánchez Sánchez, Gérôme Bovet, Burkhard Stiller, Gregorio Martínez Pérez, Alberto Huertas Celdrán

Mosaic warfare is a military strategy where reconnaissance missions with aerial vehicles are critical for gathering enemy information and achieving battlefield dominance. Nowadays, machine learning (ML) techniques play a...

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Conference paper2023

VIII Jornadas Nacionales de Investigación en Ciberseguridad (JNIC 2023)

Framework Seguro para Entrenar Modelos de Inteligencia Artificial Federados y Descentralizados

Enrique Tomás Martínez Beltrán, Pedro Miguel Sánchez Sánchez, Sergio López Bernal, Gérôme Bovet, Manuel Gil Pérez, Gregorio Martínez Pérez, Alberto Huertas Celdrán

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Related Research

COBRA V2: Gamified and Customizable Hyperrealistic Cyber Range Simulations of APTs

Nov 2025 — Jun 2026

COBRA V2: Gamified and Customizable Hyperrealistic Cyber Range Simulations of APTs

Develops adaptive training environments and realistic Advanced Persistent Threat (APT) simulation tools using gamification mechanics.

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.

ECYSAP EYE: European Cyber Situational Awareness Platform - Enhanced Cyberspace Operations

Nov 2024 — Jan 2028

ECYSAP EYE: European Cyber Situational Awareness Platform - Enhanced Cyberspace Operations

An architectural evolution of the European cyber situational awareness platform into a modular System of Systems to support military missions.