• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.37-48
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• 2014

Wireless mesh networks have emerged as a key technology in environment that needs wireless multi-hop communication without infrastructure and IEEE 802.11s mesh network standard have currently been established. One of big differences between this standard and the legacy IEEE 802.11 is that MCCA MAC is included to support QoS. MCCA supports bandwidth reservations between neighbors, so it can satisfy the QoS of bandwidth guarantee. However, MCCA has dis-advantages as follow; 1) it can not guarantee end-to-end bandwidth, 2) in multi-interface multi-channel wireless environments, the IEEE 802.11s does not provide a bandwidth reservation protocol and a wireless channel assignment etc. In this paper, we have proposed MIMC R-HWMP, which expands R-HWMP that was proposed in our previous work[3], to support multi-interface multi-channel. By simulation, we showed end-to-end bandwidth guarantee and the increase in the available bandwidth in multi-interface multi-channel wireless mesh networks.

• Strategy21
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• s.44
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• pp.5-27
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• 2018

The purpose of this paper is to look at USN's efforts to rebuild its combat power in the face of a reemergence of great powers competition, and to propose some recommendations for the ROKN. In addition to the plan to augment its fleet towards a 355-ships capacity, the USN is pursuing to improve exponentially combat lethality(quality) of its existing fleet by means of innovative science and technology. In other words, the USN is putting its utmost efforts to improve readiness of current forces, to modernize maintenance facilities such as naval shipyards, and simultaneously to invest in innovative weapons system R&D for the future. After all, the USN seems to pursue innovations in advanced military Science & Technology as the best way to ensure continued supremacy in the coming strategic competition between great powers. However, it is to be seen whether the USN can smoothly continue these efforts to rebuild combat strength vis-a-vis its new competition peers, namely China and Russian navy, due to the stringent fiscal constraints, originating, among others, from the 2011 Budget Control Act effective yet. Then, it seems to be China's unilateral and assertive behaviors to expand its maritime jurisdiction in the South China Sea that drives the USN's rebuild-up efforts of the future. Now, some changes began to be perceived in the basic framework of the hitherto regional maritime security, in the name of declining sea control of the USN as well as withering maritime order based on international law and norms. However, the ROK-US alliance system is the most excellent security mechanism upon which the ROK, as a trading power, depends for its survival and prosperity. In addition, as denuclearization of North Korea seems to take significant time and efforts to accomplish in the years to come, nuclear umbrella and extended deterrence by the US is still noting but indispensible for the security of the ROK. In this connection, the naval cooperation between ROKN and USN should be seen and strengthened as the most important deterrents to North Korean nuclear and missile threats, as well as to potential maritime provocation by neighboring countries. Based on these observations, this paper argues that the ROK Navy should try to expand its own deterrent capability by pursuing selective technological innovation in order to prevent this country's destiny from being dictated by other powers. In doing so, however, it may be too risky for the ROK to pursue the emerging, disruptive innovative technologies such as rail gun, hypersonic weapon... etc., due to enormous budget, time, and very thin chance of success. This paper recommends, therefore, to carefully select and extensively invest on the most cost-effective technological innovations, suitable in the operational environments of the ROK. In particular, this paper stresses the following six areas as most potential naval innovations for the ROK Navy: long range precision strike; air and missile defense at sea; ASW with various unmanned maritime system (UMS) such as USV, UUV based on advanced hydraulic acoustic sensor (Sonar) technology; network; digitalization for the use of AI and big data; and nuclear-powered attack submarines as a strategic deterrent.

• Journal of the Korean Society for information Management
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• v.27 no.4
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• pp.33-47
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• 2010

The growth of IT technology and the popularity of network based information sharing increase the number of digital contents in military area. Thus, there arise issues of finding suitable public information with the growing number of long-term preservation of digital public information. According to the source of raw data and the time of compilation may be variable and there can be existed in many correlations about digital contents. The business service ontology makes knowledge explicit and allows for knowledge sharing among information provider and information consumer for public digital archive engaged in improving the searching ability of digital public information. The business service ontology is at the interface as a bridge between information provider and information consumer. However, according to the difficulty of semantic knowledge extraction for the business process analysis, it is hard to realize the automation of constructing business service ontology for mapping from unformed activities to a unit of business service. To solve the problem, we propose a new business service auto-acquisition method for the first step of constructing a business service ontology based on Enterprise Architecture.

• Journal of Korean Society of Forest Science
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• v.78 no.2
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• pp.228-241
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• 1989

The objectives of this study are to identify flood disasters resulted from heavy rainstorm including earth and stone-debris avalanches and also to develope the scientific data to be needed for establishing the landslide-related disaster prevention countermeasures. For this study, 5 Gun (district) regions including Booyeo, Seochun, Gongju, Boryung, and Chungyang in Chungchongnam-do of the central part of Korea, in which severe landslide damages have been triggered during 3 days from July 21 to July 23, 1987, were investigated. Mostly, landslides having death of human lives triggered from 6 a.m, to 8 a,m. on July 22, and the principal factor was proved to be the continuous heavy rain ; the continuous rainfall of internal region for 3 days measured about 300-673 mm. The structural measures for slope failure prevention countermeasures at the hollow part of upper hillslope should be required. Natural drainage network on slopes should not be disturbed in case of land use alteration, such as a chestnut planting work on hillslopes behind the houses particularly. There are so many problems in recognition of landslide disaster prevention countermeasures including evacuation exercises. More actual education of countermeasures for control of flood and landslide should be put to practice through "civil defense education" and "inhabitants' meeting." In this context, existing Erosion Control Stations of 13 regions established in each Province should not be reduced. The designation criterion and surveying processes of "Landslide Prone Site" published by Forest Administration should also be improved scientifically.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.1-11
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• 2021

As the Internet developed, various and complex cyber attacks began to emerge. Various detection systems were used outside the network to defend against attacks, but systems and studies to detect attackers inside were remarkably rare, causing great problems because they could not detect attackers inside. To solve this problem, studies on the lateral movement detection system that tracks and detects the attacker's movements have begun to emerge. Especially, the method of using the Remote Desktop Protocol (RDP) is simple but shows very good results. Nevertheless, previous studies did not consider the effects and relationships of each logon host itself, and the features presented also provided very low results in some models. There was also a problem that the model could not explain why it predicts that way, which resulted in reliability and robustness problems of the model. To address this problem, this study proposes an interpretable RDP-based lateral movement detection system using page rank algorithm and SHAP(Shapley Additive Explanations). Using page rank algorithms and various statistical techniques, we create features that can be used in various models and we provide explanations for model prediction using SHAP. In this study, we generated features that show higher performance in most models than previous studies and explained them using SHAP.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.1-10
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• 2021

The interest in underwater acoustic sensor networks (UWASNs), along with the rapid development of underwater industries, has increased. To operate UWASNs efficiently, it is important to adopt well-designed medium access control (MAC) protocols that prevent collisions and allow the sharing of resources between nodes efficiently. On the other hand, underwater channels suffer from a narrow bandwidth, long propagation delay, and low data rate, so existing terrestrial node pairing schemes for non orthogonal multiple access (NOMA) cannot be applied directly to underwater environments. Therefore, a multi-dimensional node pairing scheme is proposed to consider the unique underwater channel in UWASNs. Conventional NOMA schemes have considered the channel quality only in node pairing. Unlike previous schemes, the proposed scheme considers the channel gain and many other features, such as node fairness, traffic load, and the age of data packets to find the best node-pair. In addition, the sender employs a list of candidates for node-pairs rather than path loss to reduce the computational complexity. The simulation results showed that the proposed scheme outperforms the conventional scheme by considering the fairness factor with 23.8% increases in throughput, 28% decreases in latency, and 5.7% improvements in fairness at best.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.149-156
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• 2021

This study started from the question of what we think about big data as the term "big data" was used and discussed in our daily lives in the era of the 4th industrial revolution. For the analysis, the final 30 Q samples were selected based on prior research related to big data, and 23 respondents were secured for Q analysis, and the following results were derived. First, the explanatory power of each type was 34.30% for , 8.03% for , 7.21% for , and 6.24% for , showing a total of 55.69%. Second, the Q sample emphasized by respondents by each type shows various occupational distributions in , and for 'big data', it is 'digital' and future'. So they were named 「Digital Type」. In , the distribution of 'social workers' was high, and for 'big data', 'future', 'collaboration', 'welfare', 'local residents', and 'defense' were emphasized. It was named 「welfare type」. In , the job distribution of respondents appeared evenly, and it was named as 「Convergence Type」. Because it emphasized statements such as 'convergence', 'digital', 'future', and 'sports'. is composed of association officials, sports instructors, and graduate students, and was named 「Artificial Intelligence Type」, because it emphasizes 'artificial intelligence', 'new paradigm', 'network', and 'sports'. In the age of knowledge industrialization and knowledge informatization that followed industrialization and informatization, how to process and utilize the numerous data accumulated over the years is an important task. Right now, in sports, more than anything else, it is necessary to continuously seek ways to utilize and activate accumulated big data.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.57-65
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• 2021

A hyper-connected intelligence information society is emerging that creates new value by converging IoT, AI, and Bigdata, which are new technologies of the fourth industrial revolution, in all industrial fields. Everything is connected to the network and data is exploding, and artificial intelligence can learn on its own and even intellectual judgment functions are possible. In particular, the Internet of Things provides a new communication environment that can be connected to anything, anytime, anywhere, enabling super-connections where everything is connected. Artificial intelligence technology is implemented so that computers can execute human perceptions, learning, reasoning, and natural language processing. Artificial intelligence is developing advanced technologies such as machine learning, deep learning, natural language processing, voice recognition, and visual recognition, and includes software, machine learning, and cloud technologies specialized in various applications such as safety, medical, defense, finance, and welfare. Through this, it is utilized in various fields throughout the industry to provide human convenience and new values. However, on the contrary, it is time to respond as intelligent and sophisticated cyber threats are increasing and accompanied by potential adverse functions such as securing the technical safety of new technologies. In this paper, we propose a new data modeling method to enable IoT integrated security control by utilizing artificial intelligence technology as a way to solve these adverse functions.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.4
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• pp.285-296
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• 2018

Among many hacking attempts carried out in the past few years, the cyber-attacks that could have caused a national-level disaster were the attacks against nuclear facilities including nuclear power plants. The most typical one was the Stuxnet attack against Iranian nuclear facility and the cyber threat targeting one of the facilities operated by Korea Hydro and Nuclear Power Co., Ltd (Republic of Korea; ROK). Although the latter was just a threat, it made many Korean people anxious while the former showed that the operation of nuclear plant can be actually stopped by direct cyber-attacks. After these incidents, the possibility of cyber-attacks against industrial control systems has become a reality and the security for these systems has been tightened based on the idea that the operations by network-isolated systems are no longer safe from the cyber terrorism. The ROK government has established a realistic control systems defense concept and in the US, the relevant authorities have set up several security frameworks to prepare for the threats. This paper presented various cyber security attack cases and their scenarios against control systems, along with the analysis of countermeasures for them. Though this task, we attempt to identify the items that need to be considered when designing a domestic security framework to improve security and secure stability.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.67-76
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• 2023

Although deep learning models are making innovative achievements in the field of computer vision, the problem of vulnerability to adversarial examples continues to be raised. Adversarial examples are attack methods that inject fine noise into images to induce misclassification, which can pose a serious threat to the application of deep learning models in the real world. In this paper, we propose a model that detects adversarial examples using differences in predictive values between edge-learned classification models and underlying classification models. The simple process of extracting the edges of the objects and reflecting them in learning can increase the robustness of the classification model, and economical and efficient detection is possible by detecting adversarial examples through differences in predictions between models. In our experiments, the general model showed accuracy of {49.9%, 29.84%, 18.46%, 4.95%, 3.36%} for adversarial examples (eps={0.02, 0.05, 0.1, 0.2, 0.3}), whereas the Canny edge model showed accuracy of {82.58%, 65.96%, 46.71%, 24.94%, 13.41%} and other edge models showed a similar level of accuracy also, indicating that the edge model was more robust against adversarial examples. In addition, adversarial example detection using differences in predictions between models revealed detection rates of {85.47%, 84.64%, 91.44%, 95.47%, and 87.61%} for each epsilon-specific adversarial example. It is expected that this study will contribute to improving the reliability of deep learning models in related research and application industries such as medical, autonomous driving, security, and national defense.