• Convergence Security Journal
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• v.6 no.4
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• pp.171-177
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• 2006

The hacking aspect of recent times is changing, the phishing attack which uses a social engineering technique is becoming the threat which is serious in Information Security. It cheats the user and it acquires a password or financial information of the individual and organization. The phishing attack uses the home page which is fabrication and E-mail and acquires personal information which is sensitive and financial information. This study proposes the establishment of National Fishing Response Center, complement of relation legal system Critical intelligence distribution channel of individual and enterprise.

• Journal of the Society of Disaster Information
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• v.1 no.1
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• pp.43-71
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• 2005

Terrorism is the use of violence, especially murder and bombing, in order to achieve political aim or to force a government to do something. Nowadays, instrument of mass destruction are smaller, cheaper, and more readily available. Cellular phones were used as timers in the attacks in Madrid last March. Hijacking an airplane is relatively inexpensive. Finally, the information revolution provides inexpensive means of communication and organization that allow groups once restricted to local and national police jurisdictions to become global. Al Qaeda is said to have established a network in fifty or more countries. These technological and ideological trends increased both the lethality and the difficulty of managing terrorism. Because of the unprecedented scale of Al Qaeda's attacks, the focus is properly on Islamic extremists. But it would be a mistake to limit our concern solely to Islamic terrorists, for that would ignore the way that technology is putting into the hands of deviant groups and individuals' destructive capabilities that were once limited primarily to governments and armies.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.

• Fourth Industrial Review
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• v.2 no.1
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• pp.19-32
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• 2022

Purpose - As new technologies that have led the 4th industrial revolution spread after the COVID-19 pandemic, the business crisis of existing financial institutions and the threat of employee jobs are growing, especially in the financial sector. The purpose of this study is to propose a human-technology convergence curriculum for creating high value-added in financial institutions and upskilling financial manpower. Research design, data, and methodology - In this study, a curriculum was designed to strengthen job competency for Private Bankers, high-quality employees of a bank dealing with high-net-worth owners. The focus of the design is that learners acquire skills to use robo-advisors as a tool and supplement artificial intelligence ethics. Result - The curriculum is organized into a total of 16 classes, and the main contents are changes in the financial environment and financial consumers, the core technology of robo-advisors and AI ethics, and establishment and evaluation of hyper-personalized asset management strategies using robo-advisors. To achieve the educational goal, two evaluations are performed to derive individual tasks and team project results. Conclusion - Human-centered upskilling convergence education will contribute to improving employee value and expanding corporate high value-added business areas by utilizing new technologies as tools. It is expected that the development and application of convergence curriculum in various fields will continue to be advanced in the future.

• Korean Security Journal
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• no.53
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• pp.63-79
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• 2017

Defence Security Command is the only military intelligence and investigation agency which is in charge of safeguarding military information and investigating specific crimes such as subversion and disloyalty in military. While the presidential security provided by Defence Security Command, along with Presidential Security Service(PSS) and the police, forms one of three pillars sustaining presidential security, its works and activities have been rarely known to the public due to the military confidentiality. This study looks into some data specialized into the presidential security among works of Defense Security Command by using various resources such as biographies of key people, media reports, and public materials. It reviews the presidential security works in a historical sense that the works have developed and changed in accordance with the historical changes of Defense Security Command, which was rooted in Counter-Intelligence Corps (Teukmubudae in Korean) in 1948 and leads to the present. The study findings are as follows. First, when the Korean War broke out in 1950 and since then the South Korea was under the threat of the North Korean armed forces and left wing forces, Counter-Intelligence Corps(Bangcheopdudae in Korean) took the lead in presidential security more than the police who was in charge of it. Secondly, even after the Presidential Security Office has founded in 1963, the role of the military on presidential security has been extended by changing its titles from Counter-Intelligence Corps to Army Security corps to Armed Forces Security Command. It has developed their provision of presidential security based on the experience at the president Rhee regime when they could successfully guard the president Rhee and the important government members. Third, since the re-establishment into Defence Security Command in 1990, it has added more security services and strengthened its legal basis. With the excellent expertise, it played a pivotal role in the G20 and other state-level events. After the establishment of the Moon Jaeinin government, its function has been reduced or abolished by the National Defense Reform Act. However, the presidential security field has been strengthening by improving security capabilities through reinforcing the organization. This strengthening of the security capacity is not only effective in coping with the current confrontation situation with the hostile North Korean regime, but also is important and necessary in conducting constant monitoring of the military movement and security-threat factors within military during the national security events.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.231-236
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• 2018

Recently, a wide variety of IoT environment is being created due to the rapid development of information and communication technology. And accordingly in a variety of network structures, a countless number of attack techniques and new types of vulnerabilities are producing a social disturbance. In May of 2018, Talos Intelligence, the Cisco threat intelligence team has newly discovered 'VPN-Filter', which constitutes a large-scale IoT-based botnet, is infecting consumer routers in over 54 countries around the world. In this paper, types of IoT-based botnets and the attack techniques utilizing botnet will be examined and the countermeasure technique through EXIF metadata removal method which is the cause of connection method of C & C Server will be proposed by examining the characteristics of attack vulnerabilities and attack scenarios of VPN-Filter.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.99-109
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• 2023

The darknet is frequently referred to as the hub of illicit online activity. In order to keep track of real-time applications and activities taking place on Darknet, traffic on that network must be analysed. It is without a doubt important to recognise network traffic tied to an unused Internet address in order to spot and investigate malicious online activity. Any observed network traffic is the result of mis-configuration from faked source addresses and another methods that monitor the unused space address because there are no genuine devices or hosts in an unused address block. Digital systems can now detect and identify darknet activity on their own thanks to recent advances in artificial intelligence. In this paper, offer a generalised method for deep learning-based detection and classification of darknet traffic. Furthermore, analyse a cutting-edge complicated dataset that contains a lot of information about darknet traffic. Next, examine various feature selection strategies to choose a best attribute for detecting and classifying darknet traffic. For the purpose of identifying threats using network properties acquired from darknet traffic, devised a hybrid deep learning (DL) approach that combines Recurrent Neural Network (RNN) and Bidirectional LSTM (BiLSTM). This probing technique can tell malicious traffic from legitimate traffic. The results show that the suggested strategy works better than the existing ways by producing the highest level of accuracy for categorising darknet traffic using the Black widow optimization algorithm as a feature selection approach and RNN-BiLSTM as a recognition model.

• Convergence Security Journal
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• v.20 no.4
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• pp.27-34
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• 2020

Recently, the fourth industrial revolution technology has not only changed everyday life greatly through technological development, but has also become a major keyword in the establishment of defense policy. In particular, Internet of Things, cloud, big data, mobile and cybersecurity technologies, called ICBMS, were selected as core leading technologies in defense information policy along with artificial intelligence. Amid the growing importance of the fourth industrial revolution technology, research is being carried out to develop the C4I system, which is currently operated separately by the Joint Chiefs of Staff and each military, including the KJCCS, ATCIS, KNCCS and AFCCS, into an integrated system in preparation for future warfare. This is to solve the problem of reduced interoperability for joint operations, such as information exchange, by operating the C4I system for each domain. In addition, systems such as the establishment of an integrated C4I system and the U.S. military's Risk Management Framework (RMF) are essential for efficient control and safe operation of weapons systems as they are being developed into super-connected and super-intelligent systems. Therefore, in this paper, the intelligent cyber threat detection, management of users' access to information, and intelligent management and visualization of cyber threat are presented in the future C4I system based on big data/cloud.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.147-155
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• 2024

Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.226-233
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• 2016

Cloud computing is a distributed computing model that has lot of drawbacks and faces difficulties. Many new innovative and emerging techniques take advantage of its features. In this paper, we explore the security threats to and Risk Assessments for cloud computing, attack mitigation frameworks, and the risk-based dynamic access control for cloud computing. Common security threats to cloud computing have been explored and these threats are addressed through acceptable measures via governance and effective risk management using a tailored Security Risk Approach. Most existing Threat and Risk Assessment (TRA) schemes for cloud services use a converse thinking approach to develop theoretical solutions for minimizing the risk of security breaches at a minimal cost. In our study, we propose an improved Attack-Defense Tree mechanism designated as iADTree, for solving the TRA problem in cloud computing environments.