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Enabling Autonomous Trust, Security and Privacy Management for IoT +

This paper presents ARCADIAN-IoT, a framework aimed at holistically enabling trust, security, privacy and recovery in IoT systems, and enabling a Chain of Trust between the different IoT entities (persons, objects and services). It builds on features such as federated AI for effective and privacy-preserving cybersecurity, distributed ledger technologies for decentralized management of trust, or transparent, user-controllable and decentralized privacy.

Illumination-aware image fusion for around-the-clock human detection in adverse environments from Unmanned Aerial Vehicle +

This study proposes a novel illumination-aware image fusion technique and a Convolutional Neural Network (CNN) called BlendNet to significantly enhance the robustness and real-time performance of small human objects detection from Unmanned Aerial Vehicles (UAVs) in harsh and adverse operation environments.

XDP-Based SmartNIC Hardware Performance Acceleration for Next-Generation Networks +

This work presents a novel framework that leverages extended Berkeley Packet Filter (eBPF) and eXpress Data Path (XDP) to offload network functions to reduce unnecessary overhead in the backbone infrastructure.

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