collaborators

6 papers

cs.DC2026

SMCC-Empowered Digital Twins for Sensorless Monitoring in Large-Scale AI-Driven IoT Systems

Vincenzo Sammartino

The deployment of AI-driven Digital Twins (DTs) in large-scale Internet-of-Things (IoT) ecosystems demands continuous, high-fidelity synchronization between the physical environmen…

cs.AI2026

QUASAR: A Quantum-Classical Neural Network for SAR Satellite Physical-Layer Authentication

Vincenzo Sammartino, Nathanael Denis, Roberto Di Pietro

X-band SAR satellites (8-12 GHz) play a critical role in disaster response, environmental monitoring, and military intelligence. Yet, they lack robust physical-layer authentication…

quant-ph2026

Feature Encoding in Quantum Machine Learning: A Survey and Practical Guidelines

Vincenzo Sammartino

The encoding of classical data into quantum states constitutes the primary performance bottleneck in Quantum Machine Learning (qml) on Noisy Intermediate-Scale Quantum (nisq) devic…

cs.CR2026

HAVE: Host Active Verification Engine for Closing the Contextual Reality Gap in Security Digital Twins

Vincenzo Sammartino, Marco Pasquini

Security Digital Twins (SDTs) provide continuously updated virtual replicas of infrastructure for threat simulation, yet they rely on theoretical CVSS scores to assign lateral-move…

cs.ET2026

SA-DTS: Semantic-Aware Digital Twin Synchronization over 6G Networks

Vincenzo Sammartino

Digital Twins (DTs) are emerging as a cornerstone of the 6G vision, enabling real-time cyber-physical mirroring for smart manufacturing, autonomous vehicles, and remote healthcare.…

cs.CR2026

Q-FE: A Quantum-Native 6G Far-Edge Architecture Securing Industrial IoT Digital Twins via CSIDH-PQC and Asynchronous Federated Learning

Vincenzo Sammartino

Sixth-generation (6G) wireless networks will underpin ultra-dense Industrial IoT (IIoT) ecosystems in which resource-constrained Far-Edge devices -- autonomous mobile robots, indus…