S-VOTE: Similarity-based Voting for Client Selection in Decentralized Federated Learning
Sánchez Sánchez, Pedro Miguel et al. (2025). "S-VOTE: Similarity-based Voting for Client Selection in Decentralized Federated Learning." IEEE IJCNN 2025.
CV
Brief CV summary.
Education
- Ph.D. in Computer Science, Cum Laude. University of Murcia, 2024
- Thesis: Identical IoT device identification via hardware performance fingerprinting and Machine Learning
- Funded by armasuisse S&T. Involved in EU-GUARDIAN EDF and 5GZORRO H2020 projects.
- M.Sc. in Computer Science, 9.07/10. University of Murcia, 2019
- Thesis: Securing Smart Offices through an Intelligent and Multi-device Continuous Authentication System
- B.Sc. in Computer Science, 8.04/10. University of Murcia, 2018
- Graduated with honors. Networking Specialization
- Thesis: Continuous authentication for mobile devices
Work experience
- Nov 2024 – Present: Senior Researcher, Funditec (Advantx Technology Foundation)
- Applied ML/DL and cybersecurity research
- Proposal writing and project execution (national and European grants)
- Feb 2024 – Nov 2024: Postdoctoral Researcher, University of Murcia
- Federated Learning methods and trustworthy AI
- Contributor to EU-GUARDIAN EDF and ROBUST-6G Horizon projects
- Sept–Dec 2021 & 2022: Visiting Researcher, Cyber-Defence Campus - armasuisse S&T
- Six month research visit as part of PhD research
- Sept 2019 – Feb 2024: Predoctoral Researcher, University of Murcia
- Research on IoT device modeling for identification and cyberattack detection
Awards and Achievements
- National Young Researcher Award in Computer Science 2024 – BBVA Foundation and SCIE Link
- Outstanding PhD Thesis Award 2024 – University of Murcia
- Elsevier Computer Networks Best Paper Award 2024
- Udacity Secure and Private AI Nanodegree Scholarship (Facebook), 2019
Skills
- Federated Learning
- AI Trustworthiness
- Machine/Deep Learning
- Cybersecurity
- IoT Behavior Analysis
- Programming:
- Python, Bash, C/C++, Java
- Frameworks: PyTorch, Keras, scikit-learn
- Courses:
- HuggingFace AI Agents
- HuggingFace NLP
- HuggingFace Computer Vision
Service and Volunteering
- Conference committee: ECAI’24 ‘25
- Conference volunteer/grant recipient: AAAI’23, ACM SIGCOMM’23, IEEE NOMS’22
Publications
ProFe: Communication-Efficient Decentralized Federated Learning via Distillation and Prototypes
Sánchez Sánchez, Pedro Miguel, Martínez Beltrán, Enrique Tomás, Fernández Llamas, Miguel, Bovet, Gérôme, Martínez Pérez, Gregorio, & Huertas Celdrán, Alberto. (2025). "ProFe: Communication-Efficient Decentralized Federated Learning via Distillation and Prototypes." IEEE ICC 2025.
Transfer Learning in Pre-Trained Large Language Models for Malware Detection Based on System Calls
Sánchez, P. M. S., Celdrán, A. H., Bovet, G., & Pérez, G. M. (2024, October). Transfer learning in pre-trained large language models for malware detection based on system calls. In MILCOM 2024-2024 IEEE Military Communications Conference (MILCOM) (pp. 853-858). IEEE.
FederatedTrust: A solution for trustworthy federated learning
Sánchez Sánchez, Pedro Miguel et al. (2024). "FederatedTrust: A solution for trustworthy federated learning." Future Generation Computer Systems, 152, 83-98.
Adversarial attacks and defenses on ML-and hardware-based IoT device fingerprinting and identification
Sánchez Sánchez, Pedro Miguel et al. (2024). "Adversarial attacks and defenses on ML-and hardware-based IoT device fingerprinting and identification." Future Generation Computer Systems, 152, 30–42.
A methodology to identify identical single-board computers based on hardware behavior fingerprinting
Sánchez Sánchez, Pedro Miguel et al. (2023). "A methodology to identify identical single-board computers based on hardware behavior fingerprinting." Journal of Network and Computer Applications, 103579.
SpecForce: A Framework to Secure IoT Spectrum Sensors in the Internet of Battlefield Things
Sánchez Sánchez, Pedro Miguel et al. (2022). "SpecForce: A Framework to Secure IoT Spectrum Sensors in the Internet of Battlefield Things." IEEE Communications Magazine.
A survey on device behavior fingerprinting: Data sources, techniques, application scenarios, and datasets
Sánchez Sánchez, Pedro Miguel et al. (2021). "A survey on device behavior fingerprinting: Data sources, techniques, application scenarios, and datasets." IEEE Communications Surveys & Tutorials, 23(2), 1048–1077.
Conferences and Talks
Decentralized Federated Learning: Enabling Collaborative AI With Enhanced Trust and Efficiency
Tutorial at 26th European Conference on Artificial Intelligence ECAI 2023, Krakow, Poland
Theoretical and Practical Intelligent Behavioral Fingerprinting
Tutorial at IEEE/IFIP Network Operations and Management Symposium, Budapest, Hungary
Intelligent Behavioral Fingerprinting - From Theory to Practice
Tutorial at 17th International Conference on Network and Service Management , Izmir, Turkey (Online due to COVID)