With the growing number of heterogeneous resource-constrained devices connected to the Internet, it becomes increasingly challenging to secure the privacy and protection of data. Strong but efficient cryptography solutions must be employed to deal with this problem, along with methods to standardize secure communications between these devices. The PRISEC module of the UbiPri middleware has this goal. In this work, we present the performance of the AES (Advanced Encryption Standard), RC6 (Rivest Cipher 6), Twofish, SPECK128, LEA, and ChaCha20-Poly1305 algorithms in Internet of Things (IoT) devices, measuring their execution times, throughput, and power consumption, with the main goal of determining which symmetric key ciphers are best to be applied in PRISEC. We verify that ChaCha20-Poly1305 is a very good option for resource constrained devices, along with the lightweight block ciphers SPECK128 and LEA.

This paper describes the new GNSS data and product services that have been developed within the context of the EPOS (European Plate Observing System) European Research Infrastructure Consortium (ERIC), which is part of the European Strategy Forum on Research Infrastructures. These services, optimized for Solid Earth research applications, endeavour to harmonise, and standardise Global Navigation Satellite System (GNSS) data collection and processing. They have been implemented by the members of the GNSS Data & Products (EPOS-GNSS), one of the Thematic Core Services (TCS) of EPOS with the active support of national and pan-European infrastructures (in particular the Regional Reference Frame Sub-Commission for Europe (EUREF) of the International Association of Geodesy). The optimized use of data from dozens of diverse European GNSS networks, installed not specifically for geodynamic studies, created additional requirements from an organizational and technical point of view, the solutions for which we describe in this article. The data flows from data suppliers and analysis centers to the various TCS Data & Product Portals are described, as well as their integration into the overall EPOS system. This is made through GLASS (GNSS Linkage Advanced Software System), a dedicated software package developed since 2016, whose architecture and functionalities are detailed here. Time series and other GNSS products computed at the several analysis centers are described as are the quality control steps that are performed. Finally, several user cases are presented that demonstrate how different stakeholders (from data providers to scientists) can benefit from the efforts being carried out by the EPOS- GNSS community.

Time–frequency (TF)-domain polarization analysis (PA) methods are widely used as a processing tool to decompose multicomponent seismic signals. However, as a drawback, they are unable to obtain sufficient resolution to discriminate between overlapping seismic phases, as they generally rely on a low-resolution time–frequency representation (TFR) method. In this article, we present a new approach to the TF-domain PA methods. More precisely, we provide an in-detailed discussion on rearranging the eigenvalue decomposition polarization analysis (EDPA) formalism in the frequency domain to obtain the frequency-dependent polarization properties from the Fourier coefficients owing to the Fourier space orthogonality. Then, by extending the formulation to the TF domain and incorporating sparsity promoting TFR (SP-TFR), we improve the resolution when estimating the TF-domain polarization parameters. Finally, an adaptive SP-TFF is applied to extract and filter different phases of the seismic wave. By processing earthquake waveforms, we show that, by combining amplitude, directivity, and rectilinearity attributes on the sparse TF-domain polarization map of the signal, we are able to extract (or filter) different phases of seismic waves. The SP-TFF method is evaluated on synthetic and real data associated with the source mechanism of the $M_{w}=8.2$ earthquake that occurred in the south-southwest of Tres Picos, Mexico. A discussion on the results is given, verifying the efficiency of the method in separating not only the Rayleigh waves from the Love waves but also in discriminating them from the body and coda waves. The codes and datasets are available at https://github.com/SigProSeismology/SP-TFF , contributing to the geoscience community.

This paper presents the research undertaken with the goal of designing a consensus algorithm for cryptocurrencies with less latency than the current state-of-the-art while maintaining a level of throughput and scalability sufficient for real-world payments. The result is Nero, a new deterministic leaderless byzantine consensus algorithm in the partially synchronous model that is especially suited for Directed Acyclic Graph (DAG)-based cryptocurrencies. In fact, Nero has a communication complexity of O($n^3$) and terminates in two message delays in the good case (when there is synchrony). The algorithm is shown to be correct, and we also show that it can provide eventual order. Finally, some performance results are given based on a proof of concept implementation in the Rust language.