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Maximizing UAV Data Efficiency in NextG Networks: A Transformer-Based mmWave Beamforming Approach
Avi Deb Raha, Apurba Adhikary, Mrityunjoy Gain, Yu Qiao, Hyeonsu Kim, Jisu Yoon, Choong Seon Hong
http://doi.org/10.5626/JOK.2025.52.2.170
Beamforming is essential in the rapidly evolving field of next generation (NextG) wireless communication, particularly when leveraging terahertz and millimeter-wave (mmWave) frequency bands to achieve ultra-high data speeds. However, these frequency bands present challenges, particularly concerning the costs associated with beam training, which can hinder Ultra-Reliable Low-Latency Communication (URLLC) in high-mobility applications, such as drone and Unmanned Aerial Vehicle (UAV) communications. This paper proposes a contextual information-based mmWave beamforming approach for UAVs and formulates an optimization problem aimed at maximizing data rates in high-mobility UAV scenarios. To predict optimal beams while ensuring URLLC, we have developed a lightweight transformerThe self-attention mechanism of the transformer allows the model to focus selectively on the most important features of the contextual information. This lightweight transformer model effectively predicts the best beams, thereby enhancing the data rates of UAVs. Simulation results demonstrate the design's effectiveness, as the lightweight transformer model significantly outperforms baseline methods, achieving up to 17.8% higher Top-1 beam accuracies and reducing average power loss by as much as 96.79%. Improvements range from 12.49% to 96.79% relative to baseline methods.
Design and Countermeasures of PowerShell-based Attack Techniques to Bypass Portable Executable Image Detection Methods
http://doi.org/10.5626/JOK.2023.50.9.813
A fileless malware attack is an advanced ever-developing attack that usually exploits script functions in PowerShell, a default Windows tool. The reason is that PowerShell allows people to access computer resources easily because its tools provide infrastructure management broadly in Windows systems. This PowerShell-based fileless malware does involve using Portable Executable(PE) images in the process of attacking. One way to identify it is by tracking and detecting the flow of PE images (i.e., DLL Injection monitoring). In this paper, we demonstrate that it is possible to execute an attack without any PE images despite using fileless malware based on PowerShell and made Proof-of-Concept malware attack codes to demonstrate this method and compare the impact of such attack. Additionally, we discussed techniques to cope with this kind of advanced malicious code.
A New Cache Replacement Policy for Improving Last Level Cache Performance
Cong Thuan Do, Dong Oh Son, Jong Myon Kim, Cheol Hong Kim
Cache replacement algorithms have been developed in order to reduce miss counts. In modern processors, the performance gap between the processor and main memory has been increasing, creating a more important role for cache replacement policies. The Least Recently Used (LRU) policy is one of the most common policies used in modern processors. However, recent research has shown that the performance gap between the LRU and the theoretical optimal replacement algorithm (OPT) is large. Although LRU replacement has been proven to be adequate over and over again, the OPT/LRU performance gap is continuously widening as the cache associativity becomes large. In this study, we observed that there is a potential chance to improve cache performance based on existing LRU mechanisms. We propose a method that enhances the performance of the LRU replacement algorithm based on the access proportion among the lines in a cache set during a period of two successive replacement actions that make the final replacement action. Our experimental results reveals that the proposed method reduced the average miss rate of the baseline 512KB L2 cache by 15 percent when compared to conventional LRU. In addition, the performance of the processor that applied our proposed cache replacement policy improved by 4.7 percent over LRU, on average.
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