• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.193-204
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• 2017

The security of Internet systems critically depends on the capability to keep anti-virus (AV) software up-to-date and maintain high detection accuracy against new malware. However, malware variants evolve so quickly they cannot be detected by conventional signature-based detection. In this paper, we proposed a malware classification method based on sequence patterns generated from the network flow of malware samples. We evaluated our method with 766 malware samples and obtained a classification accuracy of approximately 40.4%. In this study, malicious codes were classified only by network behavior of malicious codes, excluding codes and other characteristics. Therefore, this study is expected to be further developed in the future. Also, we can predict the attack groups and additional attacks can be prevented.

• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.875-884
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• 2001

Although the self organizing map (SOM) is widely utilized in such fields of data visualization and topology preserving mapping, since it should have the topology fixed before trained, it has some shortcomings that it is difficult to apply it to practical problems, and classification capability is quite low despite better clustering performance. To overcome these points this paper proposes the dynamic topology preserving self-organizing map(DTSOM) that dynamically splits the output nodes on the map and trains them, and attempts to improve the classification capability by combining multiple DTSOMs K-Winner method has been applied to combine DTSOMs which produces K outputs with winner node selection method. This produces even better performance than the conventional combining methods such as majority voting weighting, BKS Bayesian, Borda, Condorect and reliability sum. DTSOM remedies the shortcoming of determining the topology in advance, and the classification rate increases significantly by combing multiple maps trained with different features. Experimental results with handwritten digit recognition indicate that the proposed method works out to problems of conventional SOM effectively so to improve the classification rate to 98.1%.

• Journal of Korea Game Society
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• v.18 no.1
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• pp.105-114
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• 2018

Various data analysis methods used for customer type analysis are very important for game companies to understand their type and characteristics in an attempt to plan customized content for our customers and to provide more convenient services. In this paper, we propose a k-mode cluster analysis algorithm that uses information uncertainty by extending information entropy to reduce information loss. Therefore, the measurement of the similarity of attributes is considered in two aspects. One is to measure the uncertainty between each attribute on the center of each partition and the other is to measure the uncertainty about the probability distribution of the uncertainty of each property. In particular, the uncertainty in attributes is taken into account in the non-probabilistic and probabilistic scales because the entropy of the attribute is transformed into probabilistic information to measure the uncertainty. The accuracy of the algorithm is observable to the result of cluster analysis based on the optimal initial value through extensive performance analysis and various indexes.

• The Journal of the Acoustical Society of Korea
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• v.31 no.8
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• pp.542-550
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• 2012

In this paper, an adaptive scheme for network topology configuration is proposed to save the overall energy consumption in underwater acoustic sensor network. The proposed scheme employs a self-organized networking methodology where network topology is locally optimized by exchanging the energy-related information between neighboring nodes such as the remaining energy of each node, in a way that the network life time can be augmented without any centralized control function. Computer simulation is used to evaluate the proposed scheme comparing with LEACH in terms of the number of alive nodes after a given time, the deviation of individual nodes' residual energy and the energy consumption at the initialization and coordination stages.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.37-48
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• 2014

Social emotion is being highlighted as an important factor of human life in terms of quality of communication as a variety of social networks are commonly used. To understand such social emotion, this study verifies and analyzes the significance of lexical meaning and expression of emotion basically for understanding of complex meaning of social emotion. The emotional expressions represented in SNS text messages, one of the major channel of communication, are examined in this study to create scales of meaning and expression and to understand the differences deeply. As a result of the analysis, it turned out that negative assessment factors were more than positive ones among social emotional factors while positive ones were outstandingly many in the case of social emotional expression. Social emotional factors were classified by basic emotional elements and valences while emotional expression included complex meaning and especially positive elements were dominant in general.

• Aerospace Engineering and Technology
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• v.12 no.1
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• pp.87-93
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• 2013

The conceptual design lunar lander demonstrator has been developed to use as a test bed for advanced spacecraft technologies and to test a prototype planetary lander capable of vertical takeoff and landing. Size of the lunar lander demonstrator is the same as that of lunar lander conceptually designed, however, the weight of lunar lander demonstrator is designed in 1/6 scale in consideration of gravity difference between moon and earth. The thruster clustering and virtual flight test were performed in the demonstrator fixed on the ground. The demonstrator ground test has been conducted for two months in the test site for the solid motor combustion of the Goheung Flight Center. The purposes of ground test of demonstrator are to demonstrate and verify essential electronics, propulsion system, control algorithm, embedded software, structure and system operation technologies before developing the flight model lander. This paper is described about the virtual flight test including test configuration, test aims and test facilities

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5849-5855
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• 2011

As application development environment changes rapidly, importance of user interface design is increasing. Usually, most of designers are clustering by subjective method of individual to define objects that have relativity in design interface. But, interface which is designed without particular rules just adds inefficiency and complexity of business to user who use this system. Therefore, in this paper, we propose an object oriented design model that allows for flexible development by formalizing the user interface prototype in any GUI environment. The visual cohesion of the user interface is a new set of criteria which has been studied in relation to the user interface contents, and is founded on the basis of the cohesion of the interface as defined using basic software engineering concepts. The visual cohesion includes the issue of how each unit is arranged and grouped, as well as the cohesion of the business events which appear in the programming unit. The interface will become easier to understand and use if the business events are grouped by their inter-relevance within the user interface.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.859-868
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• 2004

We propose a method of selecting initial training examples for active learning so that it can reach high accuracy faster with fewer further queries. Our method is based on the assumption that an active learner can reach higher performance when given an initial training set consisting of diverse and typical examples rather than similar and special ones. To obtain a good initial training set, we first cluster examples by using k-means clustering algorithm to find groups of similar examples. Then, a representative example, which is the closest example to the cluster's centroid, is selected from each cluster. After these representative examples are labeled by querying to the user for their categories, they can be used as initial training examples. We also suggest a method of using the centroids as initial training examples by labeling them with categories of corresponding representative examples. Experiments with various text data sets have shown that the active learner starting from the initial training set selected by our method reaches higher accuracy faster than that starting from randomly generated initial training set.

• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.901-911
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• 2005

With the development of e-commerce and the proliferation of easily accessible information, information filtering has become a popular technique to prune large information spaces so that users are directed toward those items that best meet their needs and preferences. While many collaborative filtering systems have succeeded in capturing the similarities among users or items based on ratings to provide good recommendations, there are still some challenges for them to be more efficient, especially the user bias problem, non-transitive association problem and cold start problem. Those three problems impede us to capture more accurate similarities among users or items. In this paper, we provide probabilistic model approaches for UCHM and ICHM which are suggested to solve the addressed problems in hopes of achieving better performance. In this probabilistic model, objects (users or items) are classified into groups and predictions are made for users considering the Gaussian distribution of user ratings. Experiments on a real-word data set illustrate that our proposed approach is comparable with others.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1243-1258
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• 2017

A new medical materials scheduling system and its modeling method for the complex rescue are presented. Different from other similar system, first both the BeiDou Satellite Communication System (BSCS) and the Special Fiber-optic Communication Network (SFCN) are used to collect the rescue requirements and the location information of disaster areas. Then all these messages will be displayed in a special medical software terminal. After that the bipartite graph models are utilized to compute the optimal scheduling of medical materials. Finally, all these results will be transmitted back by the BSCS and the SFCN again to implement a fast guidance of medical rescue. The sole drug scheduling issue, the multiple drugs scheduling issue, and the backup-scheme selection issue are all utilized: the Kuhn-Munkres algorithm is used to realize the optimal matching of sole drug scheduling issue, the spectral clustering-based method is employed to calculate the optimal distribution of multiple drugs scheduling issue, and the similarity metric of neighboring matrix is utilized to realize the estimation of backup-scheme selection issue of medical materials. Many simulation analysis experiments and applications have proved the correctness of proposed technique and system.