Tactics, Techniques and Procedures (TTP) are valuable information to cyber-security analysts. However, they are mostly disseminated through unstructured text. This work presents a proposal for tackling this problem by using BERT models, a state-of-the-art approach in Natural Language Processing. We investigate the effect of some chosen hyperparameters on the fine-tuning of the models. MITRE's example sentences are used to train (fine-tuning step) eleven BERT models. The purpose is to find the best model and the finest combination of hyperparameters for the task of classifying TTPs according to the ATT&CK framework. As a result, we observed that the best models presented an accuracy of 82.64% and 78.75% on two datasets tested, demonstrating the potential of the application of BERT models in the complex task of TTP classification. At last, we gather some insights from the misclassified data that help better understand the dataset and how the models manage and classify the proposed data.
Due to the large available bandwidth, the communications in the terahertz band (0.1 THz − 10 THz) is one of the key techniques to meet the Tbit/s rate requirements of the future wireless networks. The propagation in the mentioned frequency range is subject to high path losses, presents a low diffractive capacity and is susceptible to diffuse scattering. Thus, in order to characterize the channel in the range from 0.2 THz to 0.3 THz, this work presents results of ray tracing simulations in an indoor environment. The ray tracing is based on the shooting-and-bouncing rays method and characterizes the propagation by means of reflections, diffractions, diffuse scattering and atmospheric molecular absorption. From the simulation results, the path losses, the Rice factor, the root-mean-square delay spread and the channel coherence band are evaluated.
The use of cryptography techniques to guarantee confidentiality, authenticity and integrity of sensitive data has become mandatory. Besides, advancements in quantum computers are gradually posing a threat to public key encryption technology. Without proper security measures, fraudsters may easily gain access to one's personal and sensitive data. The result of the third round of NIST's Post-Quantum Cryptography (PQC) process for standardization of public-key cryptography systems brought CRYSTALS-Kyber as the first mechanism selected for key encapsulation. The aim of this study is to provide the specification of a reconfigurable CRYSTAL-Kyber accelerator using High-Level Synthesis (HLS) technology. Our architecture requires about 2200 LUTs, 3001 FFs and 28 DSP on a low-cost Zynq FPGA (XC7Z020-1 CLG400C). The total time spent by the accelerator in a key exchange simulation is approximately 0.84 ms, operating at 100 MHz, and the estimated power consumption in this process is 1.695W.
This paper investigates the impact of the improved Archie's model for soil resistivity considering the volumetric water content and porosity on the transient responses developed for energization and a lightning strike applied at only one phase of the line. In this study, an overhead transmission line located on saturated sandy soil modeled by different levels of volumetric water content and porosity was assumed. The transient responses were compared to those obtained adopting a high-resistivity dry sandy soil. Results have demonstrated that the transient voltages have a significant impact on the volumetric water content and porosity for this type of soil. The pronounced variation is seen in the induced voltages for both types of disturbances.
This article presents the framework proof of concept for fault detection and identification in power electronics converters using Digital Twins. Therefore, the Digital Twins contextualization on power electronics converter is presented since it is a recent trend in this research field. Moreover, a study and classification are carried out in terms of the main failures reported by the literature on power electronics. To validate the basic methodology, a buck dc-dc power converter simulation model was elaborated on Simulink, interfaced with an external DSP, providing the link with the real time requested by such monitoring applications. The results evidence that the intentional failure scenarios in the simulation are, indeed, identified and categorized by the external DSP. Thus, this proof of concept delivers the basic step for a framework capable to provide the communication of real power converters with their respective simulation model in order to provide data comparison in the monitoring of fault situations.
