Cooperative Authentication in Underwater Acoustic Sensor Networks

With the growing use of underwater acoustic communications (UWAC) for both industrial and military operations, there is a need to ensure communication security. A particular challenge is represented by underwater acoustic networks (UWANs), which are often left unattended over long periods of time. Currently, due to physical and performance limitations, UWAC packets rarely include encryption, leaving the UWAN exposed to external attacks faking legitimate messages. In this paper, we propose a new algorithm for message authentication in a UWAN setting. We begin by observing that, due to the strong spatial dependency of the underwater acoustic channel, an attacker can attempt to mimic the channel associated with the legitimate transmitter only for a small set of receivers, typically just for a single one. Taking this into account, our scheme relies on trusted nodes that independently help a sink node in the authentication process. For each incoming packet, the sink fuses beliefs evaluated by the trusted nodes to reach an authentication decision. These beliefs are based on estimated statistical channel parameters, chosen to be the most sensitive to the transmitter-receiver displacement. Our simulation results show accurate identification of an attacker's packet. We also report results from a sea experiment demonstrating the effectiveness of our approach.Comment: Author version of paper accepted for publication in the IEEE Transactions on Wireless Communication

Indoor Millimeter Wave Localization using Multiple Self-Supervised Tiny Neural Networks

We consider the localization of a mobile millimeter-wave client in a large indoor environment using multilayer perceptron neural networks (NNs). Instead of training and deploying a single deep model, we proceed by choosing among multiple tiny NNs trained in a self-supervised manner. The main challenge then becomes to determine and switch to the best NN among the available ones, as an incorrect NN will fail to localize the client. In order to upkeep the localization accuracy, we propose two switching schemes: one based on a Kalman filter, and one based on the statistical distribution of the training data. We analyze the proposed schemes via simulations, showing that our approach outperforms both geometric localization schemes and the use of a single NN.Comment: 5 pages, 7 figures. Under Revie

ORACLE: Occlusion-Resilient and Self-Calibrating mmWave Radar Network for People Tracking

Millimeter wave (mmWave) radar sensors are emerging as valid alternatives to cameras for the pervasive contactless monitoring of people in indoor spaces. However, commercial mmWave radars feature a limited range (up to $6$-$8$ m) and are subject to occlusion, which may constitute a significant drawback in large, crowded rooms characterized by a challenging multipath environment. Thus, covering large indoor spaces requires multiple radars with known relative position and orientation and algorithms to combine their outputs. In this work, we present ORACLE, an autonomous system that (i) integrates automatic relative position and orientation estimation from multiple radar devices by exploiting the trajectories of people moving freely in the radars' common fields of view, and (ii) fuses the tracking information from multiple radars to obtain a unified tracking among all sensors. Our implementation and experimental evaluation of ORACLE results in median errors of $0.12$ m and $0.03^\circ$ for radars location and orientation estimates, respectively. Fused tracking improves the mean target tracking accuracy by $27\%$, and the mean tracking error is $23$ cm in the most challenging case of $3$ moving targets. Finally, ORACLE does not show significant performance reduction when the fusion rate is reduced to up to 1/5 of the frame rate of the single radar sensors, thus being amenable to a lightweight implementation on a resource-constrained fusion center

A Review of Indoor Millimeter Wave Device-based Localization and Device-free Sensing Technologies and Applications

The commercial availability of low-cost millimeter wave (mmWave) communication and radar devices is starting to improve the penetration of such technologies in consumer markets, paving the way for large-scale and dense deployments in fifth-generation (5G)-and-beyond as well as 6G networks. At the same time, pervasive mmWave access will enable device localization and device-free sensing with unprecedented accuracy, especially with respect to sub-6 GHz commercial-grade devices. This paper surveys the state of the art in device-based localization and device-free sensing using mmWave communication and radar devices, with a focus on indoor deployments. We first overview key concepts about mmWave signal propagation and system design. Then, we provide a detailed account of approaches and algorithms for localization and sensing enabled by mmWaves. We consider several dimensions in our analysis, including the main objectives, techniques, and performance of each work, whether each research reached some degree of implementation, and which hardware platforms were used for this purpose. We conclude by discussing that better algorithms for consumer-grade devices, data fusion methods for dense deployments, as well as an educated application of machine learning methods are promising, relevant and timely research directions.Comment: 43 pages, 13 figures. Accepted in IEEE Communications Surveys & Tutorials (IEEE COMST

Enhancing Light Harvesting by Hierarchical Functionally Graded Transparent Conducting Al-doped ZnO Nano- and Mesoarchitectures

A functionally graded Al-doped ZnO structure is presented which combines conductivity, visible transparency and light scattering with mechanical flexibility. The nano and meso-architecture, constituted by a hierarchical, large surface area, mesoporous tree-like structure evolving in a compact layer, is synthesized at room temperature and is fully compatible with plastic substrates. Light trapping capability is demonstrated by showing up to 100% improvement of light absorption of a low bandgap polymer employed as the active layer.Comment: 21 pages, 6 figures, submitted to Solar Energy Materials and Solar Cell

A validated protocol for eDNA-based monitoring of within-species genetic diversity in a pond-breeding amphibian

In light of the dramatic decline in amphibian biodiversity, new cost-efficient tools to rapidly monitor species abundance and population genetic diversity in space and time are urgently needed. It has been amply demonstrated that the use of environmental DNA (eDNA) for single-species detection and characterization of community composition can increase the precision of amphibian monitoring compared to traditional (observational) approaches. However, it has been suggested that the efficiency and accuracy of the eDNA approach could be further improved by more timely sampling; in addition, the quality of genetic diversity data derived from the same DNA has been confirmed in other vertebrate taxa, but not amphibians. Given the availability of previous tissue-based genetic data, here we use the common frog Rana temporaria Linnaeus, 1758 as our target species and an improved eDNA protocol to: (i) investigate differences in species detection between three developmental stages in various freshwater environments; and (ii) study the diversity of mitochondrial DNA (mtDNA) haplotypes detected in eDNA (water) samples, by amplifying a specific fragment of the COI gene (331 base pairs, bp) commonly used as a barcode. Our protocol proved to be a reliable tool for monitoring population genetic diversity of this species, and could be a valuable addition to amphibian conservation and wetland management

Unravelling the Band Structure and Orbital Character of a π\pi-Conjugated 2D Graphdiyne-Based Organometallic Network

Graphdiyne-based carbon systems generate intriguing layered sp-sp$^2$ organometallic lattices, characterized by flexible acetylenic groups connecting planar carbon units through metal centers. At their thinnest limit, they can result in two-dimensional (2D) organometallic networks exhibiting unique quantum properties and even confining the surface states of the substrate, which is of great importance for fundamental studies. In this work, we present the on-surface synthesis of a highly crystalline 2D organometallic network grown on Ag(111). The electronic structure of this mixed honeycomb-kagome arrangement - investigated by angle-resolved photoemission spectroscopy and scanning tunneling spectroscopy - reveals a strong electronic conjugation within the network, leading to the formation of two intense electronic band-manifolds. In comparison to theoretical density functional theory calculations, we observe that these bands exhibit a well-defined orbital character that can be associated with distinct regions of the sp-sp$^2$ monomers. Moreover, we find that the halogen by-products resulting from the network formation locally affect the pore-confined states, causing a significant energy shift. This work contributes to the understanding of the growth and electronic structure of graphdiyne-like 2D networks, providing insights into the development of novel carbon materials beyond graphene with tailored properties.Comment: 11 pages, 4 figures + supporting information (5 pages, 10 figures