Showing papers by "Alan Liu published in 2023"
01 Mar 2023
TL;DR: In this paper , a self-attention mechanism is introduced to better handle the relationship among pixels in a reflectarray for better reflectarray pattern synthesis, and the results show acceptable radiation patterns produced by the GAN model.
Abstract: In this paper, we improve the structure of a generative adversarial network (GAN) based on three fundamental characteristics of the reflectarray for synthesizing better reflectarray patterns. For meeting various challenging requirements of beamforming, we propose a new model, which uses different tactics for improvements in the generator part of a GAN model. First, for accommodating the error-sensitive characteristics of the reflectarray antenna, a fully connected network is used to increase model precision. Second, based on the effects of interference occurring among all elements in a reflectarray, a self-attention mechanism is introduced to better handle the relationship among pixels. Third, with the needs of representing the associated values of elements based on the actual physical distance between the feed horn and elements, interpolation is used to enlarge the image, and then additional convolutional layers are provided to adjust the details. The results show acceptable radiation patterns produced by the GAN model.
TL;DR: In this article , the authors focus on enhancing the security aspect of UAV system development by examining attack and defense patterns in centralized architectures and provide guidance for communities and developers working on UAV-based systems, facilitating the development of more secure and robust solutions.
Abstract: An unmanned aerial vehicle (UAV) is an autonomous flying robot that has attracted the interest of several communities because of its capacity to increase the safety and productivity of labor. In terms of software engineering, UAV system development is extremely difficult because the focus is not only on functional requirement fulfillment, but also on nonfunctional requirements such as security and safety, which play a crucial role in mission success. Consequently, architecture robustness is very important, and one of the most common architectures developed is based on a centralized pattern in which all UAVs are controlled from a central location. Even though this is a very important problem, many developers must expend a great deal of effort to adapt and improve security. This is because there are few practical perspectives of security development in the context of UAV system development; therefore, the study of attack and defense patterns in centralized architecture is required to fill this knowledge gap. This paper concentrates on enhancing the security aspect of UAV system development by examining attack and defense patterns in centralized architectures. We contribute to the field by identifying 26 attack variations, presenting corresponding countermeasures from a software analyst’s standpoint, and supplying a node.js code template for developers to strengthen their systems’ security. Our comprehensive analysis evaluates the proposed defense strategies in terms of time and space complexity, ensuring their effectiveness. By providing a focused and in-depth perspective on security patterns, our research offers crucial guidance for communities and developers working on UAV-based systems, facilitating the development of more secure and robust solutions.