• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.5
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• pp.673-681
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• 2011

Among the network information services combined with a number of security technologies and required security policies, Infrastructure as a Service, a hardware plat-form service of Cloud Computing, has been provided since 2011. It is more or less similar to the existing central concentration method services, in terms of the specifications and technical aspects for given hardware category, but it is entirely different from them in that it overcomes the spatial limitations of specific network and targets the public network. Information security technology has also been prospering so that it could ensure the stability of offered hardware plat-forms. As currently supported hardware, Internet Data Center has been provided by virtualizing the previously offered servers and discs (backup discs), but the hardware plat-forms offered are somewhat limited. Meanwhile, the areas of security fields for offered services are confined to the center or include the TCP/IP-based SSL (Secure Sockets Layer) for the public network connected with clients, which shows that microscopic access security policies have been used. Therefore, this study was aimed to provide a realistic security mechanism for realizing defense policy, by expanding service areas into security devices and suggesting Diskless and Stateless security policy based high-speed synchronous network infrastructure.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.634-638
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• 2018

Haze is a factor that degrades the performance of various image processing algorithms, such as those for detection, tracking, and recognition using an electro-optical sensor. For robust operation of an electro-optical sensor-based unmanned system used outdoors, an algorithm capable of effectively removing haze is needed. As a haze removal method using a single electro-optical sensor, the dark channel prior using statistical properties of the electro-optical sensor is most widely known. Previous methods used a square filter in the process of obtaining a transmission using the dark channel prior. When a square filter is used, the effect of removing haze becomes smaller as the size of the filter becomes larger. When the size of the filter becomes excessively small, over-saturation occurs, and color information in the image is lost. Since the size of the filter greatly affects the performance of the algorithm, a relatively large filter is generally used, or a small filter is used so that no over-saturation occurs, depending on the image. In this paper, we propose an improved haze removal method using color image segmentation. The parameters of the color image segmentation are automatically set according to the information complexity of the image, and the over-saturation phenomenon does not occur by estimating the amount of transmission based on the parameters.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.27-35
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• 2021

With the development of the Internet, various IT technologies such as IoT, Cloud, etc. have been developed, and various systems have been built in countries and companies. Because these systems generate and share vast amounts of data, they needed a variety of systems that could detect threats to protect the critical data contained in the system, which has been actively studied to date. Typical techniques include anomaly detection and misuse detection, and these techniques detect threats that are known or exhibit behavior different from normal. However, as IT technology advances, so do technologies that threaten systems, and these methods of detection. Advanced Persistent Threat (APT) attacks national or companies systems to steal important information and perform attacks such as system down. These threats apply previously unknown malware and attack technologies. Therefore, in this paper, we propose a hybrid intrusion detection system that combines anomaly detection and misuse detection to detect unknown threats. Two detection techniques have been applied to enable the detection of known and unknown threats, and by applying machine learning, more accurate threat detection is possible. In misuse detection, we applied Classification based on Association Rule(CBA) to generate rules for known threats, and in anomaly detection, we used One-Class SVM(OCSVM) to detect unknown threats. Experiments show that unknown threat detection accuracy is about 94%, and we confirm that unknown threats can be detected.

• Journal of the Korean earth science society
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• v.35 no.7
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• pp.518-528
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• 2014

In this study, a model of rainfall drop-size distribution was modified using PARSIVEL-retrieved rainfall drop-size distribution over Daegwanryeong mountainous area. A prototype model (Modified ${\Gamma}$ distribution model) applicable for this area was decided through the comparative analysis between results from models proposed by preceding research and PARSIVEL-retrieved data over Daegwanryeong mountainous area. In order to apply the prototype model for Daegwanryeong region, the parameters (${\alpha}$, A, B) were made via sensitivity experiments and models of the rainfall drop-size distributions for five cases of rainfall rate were proposed. Results from the proposed five models showed high correlations with PARSIVEL-retrieved data ($R^2=0.975$). In order to suggest a generalized form of rainfall drop-size distribution, interaction equations between rainfall rates and parameters (${\alpha}$, A, B) were investigated. The generalized model of the rainfall drop-size distribution was highly correlated with PARSIVEL-retrieved data ($R^2=0.953$), which means that the proposed model from this study was effective for simulating the rainfall drop-size distribution over Daegwanryeong region. However, the proposed model was optimized for rainfall drop-size distribution over Daegwanryeong region. Therefore, broad observations of other regions are necessary in order to develop the representative model of the Korean peninsula.

• Journal of Internet Computing and Services
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• v.11 no.6
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• pp.61-72
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• 2010

Spectrum scarcity problem and increasing spectrum demand for new wireless applications have embossed the importance of cognitive radio technology; the technology enables the sharing of channels among secondary (unlicensed) and primary (licensed) users on a non-interference basis after sensing the vacant channel. To enhance the accuracy of sensing, distributed spectrum sensing is proposed. However, it is necessary to provide the robustness against the compromised sensing nodes in the distributed spectrum sensing. RDSS, a fusion mechanism based on the reputation of sensing nodes and WSPRT (weighted sequential probability ratio test), was proposed. However, in RDSS, the execution number of WSPRT could increase according to the order of inputted sensing values, and the fast defense against the forged values is difficult. In this paper, we propose an enhanced fusion mechanism to input the sensing values in reputation order and exclude the sensing values with the high possibility to be compromised, using the trend of reputation variation. We evaluate our mechanism through simulation. The results show that our mechanism improves the robustness against attack with the smaller number of sensing values and more accurate detection ratio than RDSS.

• Journal of Convergence for Information Technology
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• v.9 no.7
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• pp.85-93
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• 2019

The purpose of this study is to identify the influence of demographic characteristics such as inappropriate lifestyle, stress, and health status among health risk factors of early adolescents according to gender. There is a gender difference in the perception of mental and physical health of early adolescents, and the result can be different in behavior patterns between men and women. This study was conducted to identify the health risk factors as independent variables for early adolescents in Daegu and Gyeongbuk area, and to analyze the determinants of gender (male, female) differences by parents, family environment, friends, academic background, appearance, grade, location, school grades, family situation, and health status as demographic factors. And, the Odds Ratio of the early adolescents was analyzed through logit analysis and the differences according to the influence relationship of each of them were examined. As a result of the analysis, the more the sleep and physical activity, parents, home environment, friends, academic background, and appearance are increased, the more the influence is likely to become on the male students. On the contrary, the rest of the health risk factors can increase, and the threat to the health risk factors is likely to become severe to the female students.Among them, it is necessary to develop a pre-preventive program for early adolescents' health risk factors, provide basic data for practical application in the field, and seek a detailed program according to the gender of early adolescents.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.61-67
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• 2024

Soldiers serving in military units and institutions are subject to strict security policies and technologies because they handle sensitive and confidential information related to national security, so they are likely to experience security stress. The purpose of this study is to recognize the need to manage the security stress of military personnel and to suggest management measures. To this end, a literature study was conducted on 12 KCI(Korean Journal Citation Index) journals dealing with security stress. Since 2016, research on security stress has been conducted mainly through empirical analysis through surveys. Studies related to security stress were divided into studies dealing with factors that affect stress, the relationship between security stress and security compliance intentions, and factors that reduce security stress. In particular, it was confirmed that factors such as organizational justice, organizational technical support, and security feedback can alleviate security stress. Next, by applying the results of this literature study to the defense security environment, we presented security stress management measures for military personnel in terms of improving security-related organizational justice awareness, technical support, and security feedback. The significance of this study is that we recognized the need to manage military personnel's security stress and reviewed practical measures related to this.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.1-12
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• 2005

Image registration is a process to establish the spatial correspondence between images of the same scene, which are acquired at different view points, at different times, or by different sensors. This paper presents a new algorithm for robust registration of the images acquired by multiple sensors having different modalities; the EO (electro-optic) and IR(infrared) ones in the paper. The two feature-based and intensity-based approaches are usually possible for image registration. In the former selection of accurate common features is crucial for high performance, but features in the EO image are often not the same as those in the R image. Hence, this approach is inadequate to register the E0/IR images. In the latter normalized mutual Information (nHr) has been widely used as a similarity measure due to its high accuracy and robustness, and NMI-based image registration methods assume that statistical correlation between two images should be global. Unfortunately, since we find out that EO and IR images don't often satisfy this assumption, registration accuracy is not high enough to apply to some applications. In this paper, we propose a two-stage NMI-based registration method based on the analysis of statistical correlation between E0/1R images. In the first stage, for robust registration, we propose two preprocessing schemes: extraction of statistically correlated regions (ESCR) and enhancement of statistical correlation by filtering (ESCF). For each image, ESCR automatically extracts the regions that are highly correlated to the corresponding regions in the other image. And ESCF adaptively filters out each image to enhance statistical correlation between them. In the second stage, two output images are registered by using NMI-based algorithm. The proposed method provides prospective results for various E0/1R sensor image pairs in terms of accuracy, robustness, and speed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.1-8
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• 2005

In this paper, we propose a two-stage head tracking algorithm adequate for real-time active camera system having pan-tilt-zoom functions. In the color convergence stage, we first assume that the shape of a head is an ellipse and its model color histogram is acquired in advance. Then, the min-shift method is applied to roughly estimate a target position by examining the histogram similarity of the model and a candidate ellipse. To reflect the temporal change of object color and enhance the reliability of mean-shift based tracking, the target histogram obtained in the previous frame is considered to update the model histogram. In the updating process, to alleviate error-accumulation due to outliers in the target ellipse of the previous frame, the target histogram in the previous frame is obtained within an ellipse adaptively shrunken on the basis of the model histogram. In addition, to enhance tracking reliability further, we set the initial position closer to the true position by compensating the global motion, which is rapidly estimated on the basis of two 1-D projection datasets. In the subsequent stage, we refine the position and size of the ellipse obtained in the first stage by using shape information. Here, we define a robust shape-similarity function based on the gradient direction. Extensive experimental results proved that the proposed algorithm performs head hacking well, even when a person moves fast, the head size changes drastically, or the background has many clusters and distracting colors. Also, the propose algorithm can perform tracking with the processing speed of about 30 fps on a standard PC.