• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.24-31
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• 2006

Traditional security mechanisms do not work well in the sensor network area due to the sensor's resource constraints. Therefore security issues are challenging problems on realization of the sensor network. Among them, the key establishment is one of the most important and challenging security primitives which establish initial associations between two nodes for secure communications. Recently, R. Anderson et al. proposed one of the promising key establishment schemes for commodity sensor network called Key Infection. However, key infection has an intrinsic vulnerability that there are some areas where adversaries can eavesdrop on the transferred key information at initial key establishment time. Therefore, in this paper, we propose a security-enhanced key establishment scheme for key infection by suggesting a mechanism which effectively reduces the vulnerable areas. The proposed security mechanism uses other neighbor nodes' additional key information to establish pair-wise key at the initial key establishment time. By using the additional key information, we can establish security-enhanced key establishment, since the vulnerable area is decreased than the key infection's. We also evaluate our scheme by comparing it with key infection using logical and mathematical analysis.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.15-28
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• 2015

As personal devices and pervasive technologies for interacting with networked objects continue to proliferate, there is an unprecedented world of scattered pieces of contextualized information available. However, the explosive growth and variety of information ironically lead users and service providers to make poor decision. In this situation, recommender systems may be a valuable alternative for dealing with these information overload. But they failed to utilize various types of contextual information. In this study, we suggest a methodology for context-aware recommender systems based on the concept of contextual boundary. First, as we suggest contextual boundary-based profiling which reflects contextual data with proper interpretation and structure, we attempt to solve complexity problem in context-aware recommender systems. Second, in neighbor formation with contextual information, our methodology can be expected to solve sparsity and cold-start problem in traditional recommender systems. Finally, we suggest a methodology about context support score-based recommendation generation. Consequently, our methodology can be first step for expanding application of researches on recommender systems. Moreover, as we suggest a flexible model with consideration of new technological development, it will show high performance regardless of their domains. Therefore, we expect that marketers or service providers can easily adopt according to their technical support.

• Journal of the Korea Institute of Building Construction
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• v.21 no.6
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• pp.677-687
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• 2021

If a fire breaks out in a building, occupants can evacuate more rapidly if they are able to identify the location of the fire, the exits, and themselves. This study derives the requirements of system development, such as distance non-limitation, a non-additional device, a non-centralized server system, and low power for an emergency, to identify information about the fire and the location of evacuees. The objective is to receive and transmit information and reduce the time and effort of the database for location tracking. Accordingly, this study develops a server-independent system that collects information related to a building fire and an evacuee's location and provides information to the evacuee on their mobile device. The system is composed of a transmitting unit to disseminate fire location information and a mobile device application to determine the locations of the fire and the evacuee. The developed system can contribute to reducing the damage to humans because evacuees can identify the location of the fire, exits, and themselves regardless of the impaired server system by fire, the interruption of power source, and the evacuee's location. Furthermore, this study proposes a theoretical basis for reducing the effort required for database construction of the k-nearest neighbor fingerprint.

• Journal of the Korean Geosynthetics Society
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• v.22 no.2
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• pp.1-12
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• 2023

Research on the causes of landslides and prediction of vulnerable areas is being conducted globally. This study aims to predict the effective soil depth, a critical element in analyzing and forecasting landslide disasters, using topographic information. Topographic data from various institutions were collected and assigned as attribute information to a 100 m × 100 m grid, which was then reduced through data grading. The study predicted effective soil depth for two cases: three depths (shallow, normal, deep) and five depths (very shallow, shallow, normal, deep, very deep). Three classification models, including K-Nearest Neighbor, Random Forest, and Deep Artificial Neural Network, were used, and their performance was evaluated by calculating accuracy, precision, recall, and F1-score. Results showed that the performance was in the high 50% to early 70% range, with the accuracy of the three classification criteria being about 5% higher than the five criteria. Although the grading criteria and classification model's performance presented in this study are still insufficient, the application of the classification model is possible in predicting the effective soil depth. This study suggests the possibility of predicting more reliable values than the current effective soil depth, which assumes a large area uniformly.

• Economic and Environmental Geology
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• v.51 no.2
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• pp.149-166
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• 2018

Many large earthquakes have continuously been reported and resulted in significant human casualties and extensive damages to properties globally. The accident of Fukushima nuclear power plant in Japan was caused by a mega-tsunami, which is a secondary effect associated with the Tohoku large earthquake (M=9.0, 2011. 3. 11.). Most earthquakes occur by reactivation of pre-existing active faults. Therefore, the importance of paleoseismological study have greatly been increased. The Korean peninsula has generally been considered to be a tectonically stable region compared with neighboring countries such as Japan and Taiwan, because it is located on the margin of the Eurasian intra-continental region. However, the recent earthquakes in Gyeongju and Pohang have brought considerable insecurity on earthquake hazard. In particular, this region should be secure against earthquake, because many nuclear facilties and large industrial facilities are located in this area. However, some large earthquakes have been reported in historic documents and also several active faults have been reported in southeast Korea. This study explains the evaluation methods of geological structures on active fault, fault damage zone, the relationship between earthquake and active fault, and respect distance. This study can contribute to selection of safe locations for nuclear facilities and to earthquake hazards and disaster prevention.

• Journal of KIISE:Databases
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• v.29 no.5
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• pp.367-380
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• 2002

Due to recent increase in applications requiring huge amount of data such as spatial data analysis and image analysis, clustering on large databases has been actively studied. In a hierarchical clustering method, a tree representing hierarchical decomposition of the database is first created, and then, used for efficient clustering. Existing hierarchical clustering methods mainly adopted the bottom-up approach, which creates a tree from the bottom to the topmost level of the hierarchy. These bottom-up methods require at least one scan over the entire database in order to build the tree and need to search most nodes of the tree since the clustering algorithm starts from the leaf level. In this paper, we propose a novel top-down hierarchical clustering method that uses multidimensional indexes that are already maintained in most database applications. Generally, multidimensional indexes have the clustering property storing similar objects in the same (or adjacent) data pares. Using this property we can find adjacent objects without calculating distances among them. We first formally define the cluster based on the density of objects. For the definition, we propose the concept of the region contrast partition based on the density of the region. To speed up the clustering algorithm, we use the branch-and-bound algorithm. We propose the bounds and formally prove their correctness. Experimental results show that the proposed method is at least as effective in quality of clustering as BIRCH, a bottom-up hierarchical clustering method, while reducing the number of page accesses by up to 26～187 times depending on the size of the database. As a result, we believe that the proposed method significantly improves the clustering performance in large databases and is practically usable in various database applications.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.625-634
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• 2002

In this paper, we conducted various experiments with Bayesian networks in order to analyze clinical data of infertility patients. With these experiments, we tried to find out inter-dependencies among important factors playing the key role in clinical pregnancy, and to compare 3 different kinds of Bayesian network classifiers (including NBN, BAN, GBN) in terms of classification performance. As a result of experiments, we found the fact that the most important features playing the key role in clinical pregnancy (Clin) are indication (IND), stimulation, age of female partner (FA), number of ova (ICT), and use of Wallace (ETM), and then discovered inter-dependencies among these features. And we made sure that BAN and GBN, which are more general Bayesian network classifiers permitting inter-dependencies among features, show higher performance than NBN. By comparing Bayesian classifiers based on probabilistic representation and reasoning with other classifiers such as decision trees and k-nearest neighbor methods, we found that the former show higher performance than the latter due to inherent characteristics of clinical domain. finally, we suggested a feature reduction method in which all features except only some ones within Markov blanket of the class node are removed, and investigated by experiments whether such feature reduction can increase the performance of Bayesian classifiers.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.103-112
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• 2010

In sensor networks, because sensors are deployed in an unprotected environment, they are prone to be targets of compromise attack, If the number of compromised nodes increases considerably, the key management in the network is paralyzed. In particular, compromise of Cluster Heads (CHs) in clustered sensor networks is much more threatening than that of normalsensors. Recently, rekeying schemes which update the exposed keys using the keys unknown to the compromised nodes are emerging. However, they cause some security and efficiency problems such as single group key employment in a cluster, passive eviction of compromised nodes, and excessive communication and computation overhead. In this paper, we present a proactive rekeying scheme using renewals of duster organization for clustered sensor networks. In the proposed scheme, each sensor establishes individual keys with neighbors at network boot-up time, and these keys are employed for later transmissions between sensors and their CH. By the periodic cluster reorganization, the compromised nodes are expelled from network and the individual keys employed in a cluster are changed continuously. Besides, newly elected CHs securely agree a key with sink by informing their members to sink, without exchangingany keying materials. The simulation results shows that the proposed scheme remarkably improves the confidentiality and integrity of data in spite of the increase of compromised nodes. Also, they show that the proposed scheme exploits the precious energy resource more efficiently than SHELL.

• Journal of the Korean Geographical Society
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• v.43 no.4
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• pp.655-679
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• 2008

This study is to analyze the base of selection and feature of description on Korea-related content in Japanese curriculum(geography and history) and high-school geography textbooks. Japanese curriculum requires that there are two or three neighbor countries to be selected and their contents consist of life and culture and have to compare with those of japan in view of understanding and respect on similarity and difference. The content of physical environment is only dealt as factors influencing on life and culture because regional teaming of neighbor countries focus on it. Dok-do is described with conflict region in most of textbooks. But some textbooks describe Dok-do with territory of Shimane-Hyun in Japan or devide like japanese territory on the map. There are described han-gul(Korean language), confucianism, buddhism and christianity, han-bok(Korean clothes), rice and soup, bulgogi(Korean meat dishes) and scissors, spoon and chopsticks, ondol(Korean floor heater), etc. with the cases of specific Korean life and culture. And, exchange between Korea and Japan focuses on more cultural view increasing recently than political and economical view. Then Japanese high-school geography textbooks humanize geography because of they focus on life and culture and promote not only knowledge and understanding but also altruism and empathy because they focus on similarity and difference through comparison between neighbor country and Japan. This shows how to able to practice regional teaming in globalization and multicultural society.

• Journal of KIISE
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• v.42 no.11
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• pp.1441-1451
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• 2015

As one of the most spotlighted research areas, these days, the Internet of Things (IoT) aims to provide users with various services through many devices. Since there exist so many devices in IoT environments, it is inefficient to manually configure the domain name system (DNS) names of such devices. Thus, for IPv6-based IoT environments, this paper proposes a scheme called the DNS Name Autoconfiguration (DNSNA) that autoconfigures an IoT device's DNS name and manages it. In the procedure for generating and registering an IoT device's DNS name, the standard protocols of the Internet Engineering Task Force (IETF) are used. Since the proposed scheme resolves an IoT device's DNS name into an IPv6 address in unicast through a DNS server, it generates less traffic than multicast-based mDNS (Multicast DNS) which is a legacy DNS application for the DNS name service in the smart home. Thus, the proposed scheme is more appropriate in multi-hop IoT networks than mDNS. This paper explains the design of the proposed scheme and its service scenarios, such as smart home and smart road. It also explains the implementation and testing of the proposed scheme in the smart grid.