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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. 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

Quick facts

Year
2023
Venue
MILCOM 2023 - 2023 IEEE Military Communications Conference (MILCOM)
Identifier
sanchezsanchez2023stealth

Suggested citation

Pedro Miguel Sánchez Sánchez, Enrique Tomás Martínez Beltrán, Alberto Huertas Celdrán, Robin Wassink, Gérôme Bovet, Gregorio Martínez Pérez, Burkhard Stiller (2023). Stealth Spectrum Sensing Data Falsification Attacks Affecting IoT Spectrum Monitors on the Battlefield. MILCOM 2023 - 2023 IEEE Military Communications Conference (MILCOM).

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

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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

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.