This paper proposes a new method for estimating the reliability of machine learning predictions applied to Earth observation (EO) and health-related datasets, with a focus on forecasting mosquito abundance (MA). The authors develop a Variational Autoencoder (VAE)-based confidence metric that… Read More »A Latent Space Metric for Enhancing Prediction Confidence in Earth Observation Data
This paper proposes a lightweight wireless intrusion detection method that identifies 5G jamming attacks using spectrograms derived directly from received IQ samples. Instead of relying on higher-layer metrics like PER or SINR which can fluctuate naturally and often fail to… Read More »Detecting 5G Signal Jammers Using Spectrograms with Supervised and Unsupervised Learning
In this paper, the authors propose a physical-layer challenge–response authentication (CR-PLA) protocol designed specifically for drone communication. Instead of relying on cryptographic keys, the receiver drone (Bob) authenticates the sender by exploiting location-dependent wireless channel attenuation, influenced by path loss… Read More »Energy-Based Optimization of Physical-Layer Challenge-Response Authentication with Drones
In this paper, a challenge–response physical-layer authentication (CR-PLA) scheme is proposed in which the receiver uses an Intelligent Reflecting Surface (IRS) to validate the identity of a single-antenna transmitter. The method operates by randomly selecting IRS phase configurations and checking… Read More »Physical-Layer Challenge-Response Authentication with IRS and Single-Antenna Devices
This paper analyzes a new attack strategy targeting challenge–response physical layer authentication (CR-PLA) systems that rely on intelligent reflecting surfaces (IRSs). The authors extend prior KL-divergence–based bounds for conventional PLA to the CR-PLA setting, where Bob randomizes the IRS phase… Read More »Divergence-Minimizing Attack Against Challenge-Response Authentication with IRSs
This paper investigates a physical layer authentication (PLA) scheme designed to overcome the limitations of traditional cryptographic approaches in large-scale and heterogeneous wireless networks, particularly for resource-constrained IoT devices. The proposed method introduces a reconciliation-based approach that leverages distributed source coding (Slepian-Wolf) with polar… Read More »Physical Layer Authentication Using Information Reconciliation
In this paper, the feasibility of implementing a lightweight key distribution scheme using physical layer security for secret key generation (SKG) is explored. Specifically, we focus on examining SKG with the received signal strength (RSS) serving as the primary source… Read More »Secret Key Generation Rates for Line of Sight Multipath Channels in the Presence of Eavesdroppers
As 6G networks promise unparalleled connectivity with ultra-low latency, high bandwidth, and multi-domain interoperability, they also face an increasingly complex security landscape. The integration of advanced AI/ML-driven automation in network management introduces new opportunities but also heightens the potential risks… Read More »Enhancing 6G Security with Zero-Touch Automation: Insights from ROBUST-6G Deliverable 4.1
As global connectivity ushers in the next era of communication, 6G networks are poised to revolutionize technology with unprecedented capabilities. These advancements will rely heavily on Artificial Intelligence (AI) and Machine Learning (ML), which are expected to enhance network efficiency,… Read More »Strengthening 6G AI/ML Security: Insights from ROBUST-6G Threat Assessment and Prevention Report
As the world transitions towards the sixth generation (6G) of wireless networks, ensuring robust security and trustworthiness solutions becomes a critical necessity. In this vein, the ROBUST-6G project aims to address key challenges related to security and trustworthiness through a… Read More »Exploring the Future of Secure 6G Networks: Insights from ROBUST-6G Deliverable 2.2