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This work presents a novel Field Programmable Gate Array (FPGA)-based architecture for encrypting telemetry together with high-definition video data in unmanned aerial vehicles (UAVs). The design uses the Advanced Encryp...

Abstract We present a continuous-variable (CV), quantum-key-distribution (QKD)—inspired, keyed physical-layer masking method for classical M-level pulse-amplitude-modulation (M-PAM) links. A transmitter adds a per-symb...

ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐...

Abstract Federated Learning (FL) has been widely used in Internet of Things (IoT) environments as a promising decentralized framework capable of collaborative model training without exposing local data. Despite its advan...

Abstract The explosion of patient data, the demand for real-time insights, and the critical importance of data security drive healthcare innovation. Medical Internet of Things (IoMT) offers a promising solution, connecti...

In order to improve digital resilience, privacy, and access equity in contemporary library environments, this study investigates the role of Virtual Private Networks (VPNs) in fostering sustainable cybersecurity within t...

Robot Operating System (ROS) is a middleware widely used in robotics development. ROS simplifies communication between nodes within a network so that robot developers are able to simply develop robot applications. Howeve...

Abstract The increasing adoption of Industrial Internet of Things (IIoT) devices introduces significant cybersecurity and privacy challenges, particularly anomaly detection and secure data sharing. This study presents Se...

Abstract Smart home networks are a rapidly evolving part of the Internet of Things (IoT), where connected devices exchange information to automate energy use, enhance comfort, and improve user safety. Despite their benef...

Federated Learning (FL) has emerged as a privacy-preserving distributed learning paradigm that enables collaborative model training without sharing raw data. Despite its advantages, ensuring trustworthy FL deployment rem...

Abstract The rapid adoption of encrypted communication protocols has raised privacy levels but has also dealt a significant blow to traditional intrusion detection systems that rely on payload inspection for anomaly dete...