• Journal of Information Processing Systems
• /
• v.15 no.4
• /
• pp.865-889
• /
• 2019

The need for cyber resilience is increasingly important in our technology-dependent society where computing devices and data have been, and will continue to be, the target of cyber-attackers, particularly advanced persistent threat (APT) and nation-state/sponsored actors. APT and nation-state/sponsored actors tend to be more sophisticated, having access to significantly more resources and time to facilitate their attacks, which in most cases are not financially driven (unlike typical cyber-criminals). For example, such threat actors often utilize a broad range of attack vectors, cyber and/or physical, and constantly evolve their attack tactics. Thus, having up-to-date and detailed information of APT's tactics, techniques, and procedures (TTPs) facilitates the design of effective defense strategies as the focus of this paper. Specifically, we posit the importance of taxonomies in categorizing cyber-attacks. Note, however, that existing information about APT attack campaigns is fragmented across practitioner, government (including intelligence/classified), and academic publications, and existing taxonomies generally have a narrow scope (e.g., to a limited number of APT campaigns). Therefore, in this paper, we leverage the Cyber Kill Chain (CKC) model to "decompose" any complex attack and identify the relevant characteristics of such attacks. We then comprehensively analyze more than 40 APT campaigns disclosed before 2018 to build our taxonomy. Such taxonomy can facilitate incident response and cyber threat hunting by aiding in understanding of the potential attacks to organizations as well as which attacks may surface. In addition, the taxonomy can allow national security and intelligence agencies and businesses to share their analysis of ongoing, sensitive APT campaigns without the need to disclose detailed information about the campaigns. It can also notify future security policies and mitigation strategy formulation.

• Convergence Security Journal
• /
• v.18 no.2
• /
• pp.89-99
• /
• 2018

In the year 2018, South Korea faces a crucial decision with regard to reunification. Starting from inter-Korean and US-North summits held from April through June, A rough journey for North Korea's "Complete, verifiable and irreversible dismantlement" began. Although South Korea insists that North Korea's Nuclear 'CVID' is the only minimum condition in the process of peaceful reunification, North Korea and other countries who support North Korea, including China and Russia, will possibly claim that North Korea's Nuclear 'CVID' will minimize their political and military positions internationally. Despite representatives from each country agreeing to North Korea's denuclearization, it is inevitable that many challenges still need to be resolved during the process. From the perspective of the Chinese government, North Korea is not a country that stimulates international conflicts. Instead, China can utilize North Korea as their political and tactical leverage against the US in order to compete for hegemonic power in Asia. In order to reject the emerging supremacy of China and resolve uncertainties in the denuclearization agreement and implementation process, I suggest the necessity of 'Korea-Japan Security Cooperation' as a 'second alternative' to achieve the North Korea's Nuclear 'CVID'.

• International Journal of High-Rise Buildings
• /
• v.8 no.2
• /
• pp.107-116
• /
• 2019

The use of computational fluid dynamics (CFD) is becoming an increasingly popular means to model wind flows in and around buildings. The first published application of CFD to both indoor and outdoor building airflows was in the 1970's. Since then, CFD usage has expanded to include different aspects of building design. Wind tunnel testing (WTT) on buildings for wind loads goes back as far as 1908. Gustave Eiffel built a pair of wind tunnels in 1908 and 1912. Using these he published wind loads on an aircraft hangar in 1919 as cited in Hoerner (1965 - page 74). The second of these wind tunnels is still in use today for tests including building design ($Damljanovi{\acute{c}}$, 2012). The Empire State Building was tested in 1933 in smooth flow - see Baskaran (1993). The World Trade Center Twin Towers in New York City were wind tunnel tested in the mid-sixties for both wind loads, at Colorado State University (CSU) and the [US] National Physical Laboratory (NPL), as well as pedestrian level winds (PLW) at the University of Western Ontario (UWO) - Baskaran (1993). Since then, the understanding of the planetary boundary layer, recognition of the structures of turbulent wakes, instrumentation, methodologies and analysis have been continuously refined. There is a drive to replace WTT with computational methods, with the rationale that CFD is quicker, less expensive and gives more information and control to the architects. However, there is little information available to building owners and architects on the limitations of CFD for flows around buildings and communities. Hence building owners, developers, engineers and architects are not aware of the risks they incur by using CFD for different studies, traditionally conducted using wind tunnels. This paper will explain what needs to happen for CFD to replace wind tunnels. Ultimately, we anticipate the reader will come to the same conclusion that we have drawn: both WTT and CFD will continue to play important roles in building and infrastructure design. The most pressing challenge for the design and engineering community is to understand the strengths and limitations of each tool so that they can leverage and exploit the benefits that each offers while adhering to our moral and professional obligation to hold paramount the safety, health, and welfare of the public.

• Smart Media Journal
• /
• v.11 no.4
• /
• pp.30-37
• /
• 2022

Disease threatens plant growth and recognizing the type of disease is essential to making a remedy. In recent years, deep learning has witnessed a significant improvement for this task, however, a large volume of labeled images is one of the requirements to get decent performance. But annotated images are difficult and expensive to obtain in the agricultural field. Therefore, designing an efficient and effective strategy is one of the challenges in this area with few labeled data. Transfer learning, assuming taking knowledge from a source domain to a target domain, is borrowed to address this issue and observed comparable results. However, current transfer learning strategies can be regarded as a supervised method as it hypothesizes that there are many labeled images in a source domain. In contrast, unsupervised transfer learning, using only images in a source domain, gives more convenience as collecting images is much easier than annotating. In this paper, we leverage unsupervised transfer learning to perform plant disease recognition, by which we achieve a better performance than supervised transfer learning in many cases. Besides, a vision transformer with a bigger model capacity than convolution is utilized to have a better-pretrained feature space. With the vision transformer-based unsupervised transfer learning, we achieve better results than current works in two datasets. Especially, we obtain 97.3% accuracy with only 30 training images for each class in the Plant Village dataset. We hope that our work can encourage the community to pay attention to vision transformer-based unsupervised transfer learning in the agricultural field when with few labeled images.

• East Asian Economic Review
• /
• v.26 no.1
• /
• pp.49-91
• /
• 2022

Recent years have witnessed renewed interest in Africa and public diplomacy has emerged as the vital tool being used to cultivate these relations. China has been leading in pursuing stronger economic partnership with Africa while middle powers such as Korea are also intensifying engagement with the continent. While previous studies have analyzed the implications of China's activities in Africa on advanced powers, none has examined them from the paradigm of middle powers. This study fills this gap by assessing China's activities in Africa, their economic engagement and implications for Korea's interest in Africa. The analysis is qualitative based on secondary data from various sources and literature. The study shows that China's public diplomacy strategy involves a high degree of innovation and has evolved to encompass new tools and audiences. China has institutionalized a cooperative model that permeates many aspects of governance institutions in Africa, enabling it to strengthen their relations. This could also be helping China to adjust faster leadership transitions in Africa. Whereas the US is still the most influential country in Africa, China is influential in economic policies and has outstripped the US in infrastructure diplomacy. This could be because African policy makers align more with China's economic model than the US' mainstream economics. Chinese aid to Africa has been diversified to social sectors that are more responsive to the needs of Africa. Trade and investment relations between China and Africa have deepened, but so does trade imbalance since 2010. China mainly imports natural resources and raw materials from Africa. But this product portfolio is not different from Korea and the US. China's energetic insertion in Africa using various strategies has significant implications for countries with ambitions in Africa. Korea can achieve its ambitions in Africa by focusing resources in areas it can leverage its core strengths-such as education and vocational training, environmental policy and development cooperation.

• Journal of Korea Multimedia Society
• /
• v.25 no.1
• /
• pp.1-9
• /
• 2022

Ship detection in synthetic aperture radar (SAR) images is an important application in marine monitoring for the military and civilian domains. Over the past decade, object detection has achieved significant progress with the development of convolutional neural networks (CNNs) and lot of labeled databases. However, due to difficulty in collecting and labeling SAR images, it is still a challenging task to solve SAR ship detection CNNs. To overcome the problem, some methods have employed conventional data augmentation techniques such as flipping, cropping, and affine transformation, but it is insufficient to achieve robust performance to handle a wide variety of types of ships. In this paper, we present a novel and effective approach for deep SAR ship detection, that exploits label-rich Electro-Optical (EO) images. The proposed method consists of two components: a data augmentation network and a ship detection network. First, we train the data augmentation network based on conditional generative adversarial network (cGAN), which aims to generate additional SAR images from EO images. Since it is trained using unpaired EO and SAR images, we impose the cycle-consistency loss to preserve the structural information while translating the characteristics of the images. After training the data augmentation network, we leverage the augmented dataset constituted with real and translated SAR images to train the ship detection network. The experimental results include qualitative evaluation of the translated SAR images and the comparison of detection performance of the networks, trained with non-augmented and augmented dataset, which demonstrates the effectiveness of the proposed framework.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.5
• /
• pp.959-968
• /
• 2022

In this paper, we intend to develop a cart with the convenience of moving objects or items that are difficult to hold by the hand of the disabled and the elderly from outdoor activities to a moving location. Using GPS module, DC motor, Bluetooth module, magnetometer sensor, and Blynk application, the smart follow cart was programmed to accurately know the owner's location while following the cart. The values of latitude and longitude of the magnetometer sensor are set so that the correct leverage value can be obtained in the lead for fine adjustment of the start and stop angles so that the user's position can be freely detected. The above motor driver L298n was connected to the motor to drive the DC motor at a fine angle. A smart follow cart was implemented that receives location signals according to the direction of the owner by turning on/off the mobile phone app as a switching role by connecting the GPS through Bluetooth wireless communication using a smartphone.

• Journal of Korea Trade
• /
• v.25 no.1
• /
• pp.65-88
• /
• 2021

Purpose - This paper aims to examine the determinants of SWFs' investment in Asian countries and to identify consistent investment patterns of SWFs in specific target firms from Asia, particularly China and South Korea. Design/methodology - This study extends the Tobin's Q model to examine the relationship between SWF investments in target firms and their returns with other firm-level control variables. We collect consistent data on SWF investments and the matched firm-level data on target firms, which of observation is 1,512 firms (333 in South Korea and 1,179 in China) targeted by 20 SWF sources during 1997-2017. The panel random effect model is used to estimate the extended Tobin's Q model. The robustness of the estimations is tested by the simultaneous equation models and the panel GEE model. Findings - The evidence shows that sovereign wealth funds are more inclined to invest in the financial sector with a monopoly position and in large firms with higher growth opportunity and superior cash asset ratios in China. In contrast to their investments in China, sovereign wealth funds in South Korea prefer to invest in strategic sectors, such as energy and information technology, and in large firms with high performance and low leverage. Sovereign wealth funds' investments tend to significantly improve the target firm's performance measured by sales growth and returns in both Korea and China. Originality/value - The existing literature focuses on examining the determination of SWFs investment in the developed countries, such as Europe and the United States. Our paper contributes to the literature in three ways; first, we analyzes case studies of SWF investments in Asian markets, which are less developed and riskier. Second, we examine whether the determination of SWF investment in Asian target firms depends on the different time periods, on types of sources of SWFs, and on acquiring countries. Third, our research uses vast sample data on target firms in longer time periods (1997-2017) than other previous studies on the SWFs for Asian markets.

• The Journal of the Korea Contents Association
• /
• v.21 no.7
• /
• pp.328-339
• /
• 2021

In the age of global competition, city brand is a significant element for establishing a city's competitiveness. City branding is the process of building a storytelling about cities' content. Among the various contents that differentiate cities, this study seeks to discuss the role of an event and a city brand in the process of city branding based on the city marketing and event tourism literatures. This research uses grounded theory and a case study to examine Seoul exploring the changes in the Hi Seoul Festival and the Hi Seoul city brand over the last two decades. The qualitative research includes a secondary data analysis based on case studies from domestic and foreign regions and their festivals. The analytical results indicted three limitations: inconsistency, a lack of identity, and political leverage. Based on the limitations, this study discusses the importance of the connection between city identity and event content, suggesting implications for moving forward toward a stable Seoul city branding strategy for the Seoul Metropolitan Government.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.11
• /
• pp.3950-3969
• /
• 2021

Radio Frequency (RF)-based indoor localization technologies play significant roles in various Internet of Things (IoT) services (e.g., location-based service). Most such technologies require that all the devices comply with a specified technology (e.g., WiFi, ZigBee, and Bluetooth). However, this requirement limits its application scenarios in today's IoT context where multiple devices complied with different standards coexist in a shared environment. To bridge the gap, in this paper, we propose a cross-technology localization approach, which is able to localize target nodes using a different type of devices. Specifically, the proposed framework reuses the existing WiFi infrastructure without introducing additional cost to localize Non-WiFi device (i.e., ZigBee). The key idea is to leverage the interference between devices that share the same operating frequency (e.g., 2.4GHz). Such interference exhibits unique patterns that depend on the target device's location, thus it can be leveraged for cross-technology localization. The proposed framework uses Principal Components Analysis (PCA) to extract salient features of the received WiFi signals, and leverages Dynamic Time Warping (DTW), Gradient Boosting Regression Tree (GBRT) to improve the robustness of our system. We conduct experiments in real scenario and investigate the impact of different factors. Experimental results show that the average localization accuracy of our prototype can reach 1.54m, which demonstrates a promising direction of building cross-technology technologies to fulfill the needs of modern IoT context.