• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.363-372
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• 2022

Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.923-932
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• 1997

In this paper, we propose a two-level hybrid signature file method(THM) to dffciently deal with large txt databases that use a term discrimination concept.In addition, we apply Yoo's clustering scheme to the two-level hybeid signature file method. The clustering schme groups similar signatures together according to the similarity of the highly discriminatiory tems so that we may achive better performance on retrival. The space-time ana-lyhtical model of the proposed two-level hybrid method is provided. Based on the analytical model and experiments, we compare it with the exsting methods, i.e. the bit-sliced method(BM), the-level method(TM), and the hybrid method(HM). As a result, we show that THM achives the best retrival performance in a large database with 100,000 records when the mumber fo matching records is less than 160.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.15-40
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• 2020

Due to the explosive growth of mobile application services, categorizing mobile application services is in need in practice from both customers' and developers' perspectives. Despite the fact, however, there have been limited studies regarding systematic categorization of mobile application services. In response, this study proposed a method for categorizing mobile application services, and suggested a service taxonomy based on the network clustering results. Total of 1,607 mobile healthcare services are collected through the Google Play store. The network analysis is conducted based on the similarity of descriptions in each application service. Modularity detection analysis is conducted to detects communities in the network, and service taxonomy is derived based on each cluster. This study is expected to provide a systematic approach to the service categorization, which is helpful to both customers who want to navigate mobile application service in a systematic manner and developers who desire to analyze the trend of mobile application services.

• The Journal of Korean Medicine
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• v.41 no.1
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• pp.11-20
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• 2020

Objectives: We noticed that hyperhidrosis can be differentiated by whether it is topical or systemic in both Korean medicine(KM) and Modern medicine(MM). Comparing between topical and systemic sweating, we will figure out similarity between KM and MM about stimuli on sweat. Methods: All research is done by finding information on text-book, article, books. Results: Hyperhidrosis is differentiated by whether it is topical or systemic in both Korean medicine(KM) and Modern medicine(MM). First, systemic sweating(SS) is affected by body temperature. In KM, Heat and Cold(plus yang deficiency) can make human sweat systemically. In MM, heat is also mentioned as stimulus. Second, topical sweating(TS) can occur on emotionally-stressed situation especially on palms-and-soles. In KM, this phenomenon is explained by heart spirit(心神) and disease transmitted by pericardium meridian(手厥陰心包經 是動病). In MM, anatomically hyperhidrosis on palms-and-soles is generated by adrenergic sympathetic nerve which is involved with stress. Third, sweating on palms-and-soles also can be generated by internal organ. In KM, hyperhidrosis on palms-and-soles is explained as illness on stomach meridian(足陽明胃經). The 70% of parasympathetic nerve is vagus nerve which is located at internal organs-usually gastrointestinal tract. In that point, stomach and parasympathetic nerve seem to be involved in hyperhidrosis on palms-and-soles. Conclusion: Hyperhidrosis is differentiated similarly by whether it is topical or systemic in both Korean medicine and Modern medicine. Conserving each perspective of KM and MM, one perspective can be useful to other by supplementing other's weak point.

• Journal of the Korean Society for information Management
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• v.30 no.3
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• pp.23-48
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• 2013

This study compared and analyzed 15 CBMR (Content-based Music Retrieval) systems accessible on the web in terms of DB size and type, query type, access point, input and output type, and search functions, with reviewing features of music information and techniques used for transforming or transcribing of music sources, extracting and segmenting melodies, extracting and indexing features of music, and matching algorithms for CBMR systems. Application of text information retrieval techniques such as inverted indexing, N-gram indexing, Boolean search, truncation, keyword and phrase search, normalization, filtering, browsing, exact matching, similarity measure using edit distance, sorting, etc. to enhancing the CBMR; effort for increasing DB size and usability; and problems in extracting melodies, deleting stop notes in queries, and using solfege as pitch information were found as the results of analysis.

• The Journal of Information Systems
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• v.29 no.3
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• pp.237-251
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• 2020

Purpose The research was studied the hierarchical Hangul emotion index by organizing all the emotions which SNS users are thinking. As a preliminary study by the researcher, the English-based Plutchick (1980)'s emotional standard was reinterpreted in Korean, and a hashtag with implicit meaning on SNS was studied. To build a multidimensional emotion dictionary and classify three-dimensional emotions, an emotion seed was selected for the composition of seven emotion sets, and an emotion word dictionary was constructed by collecting SNS hashtags derived from each emotion seed. We also want to explore the priority of each Hangul emotion index. Design/methodology/approach In the process of transforming the matrix through the vector process of words constituting the sentence, weights were extracted using TF-IDF (Term Frequency Inverse Document Frequency), and the dimension reduction technique of the matrix in the emotion set was NMF (Nonnegative Matrix Factorization) algorithm. The emotional dimension was solved by using the characteristic value of the emotional word. The cosine distance algorithm was used to measure the distance between vectors by measuring the similarity of emotion words in the emotion set. Findings Customer needs analysis is a force to read changes in emotions, and Korean emotion word research is the customer's needs. In addition, the ranking of the emotion words within the emotion set will be a special criterion for reading the depth of the emotion. The sentiment index study of this research believes that by providing companies with effective information for emotional marketing, new business opportunities will be expanded and valued. In addition, if the emotion dictionary is eventually connected to the emotional DNA of the product, it will be possible to define the "emotional DNA", which is a set of emotions that the product should have.

• The Research Journal of the Costume Culture
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• v.17 no.1
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• pp.132-148
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• 2009

The objective of this article is to examine the possibility of 'story-telling' as united concept of causality and subjectivity through sequence combination, and the 'similarity' between object and image in fashion photographs making diversity of meanings. To analyze and investigate the research, as evidential data this paper used the photos of Steven Meisel from 2002 till 2007 Vogue published in Korea, U.S, and Italy, as well as other visual data like graphic collections, catalogs, art-related data and internet data. This research runs both theoretical and positive investigations to suggest the function of story-telling in the Process of opened-communicative roles of fashion photos. Thus this paper investigated Steven Meisel's storytelling in his fashion photos; short moment of event, continuity of time, compound of sequence, and complexity of viewpoint. This paper also studied the aesthetic characteristics of Steven Meisel's fashion photos as categories of overlapped meaning, arbitrariness of interpretation, exclusivity of message, and decoding. The research result suggests that clothing not only includes current age's value but also among social constitutions it includes multilateral characteristics. Ultimately this paper is also making meaning alive by cutting off the chain of 'firm' meanings of fashion photo. That seems like opening the opportunity for correctly understanding fashion's meaning which has the aspects of ambivalence of changing meanings and values by the motivation of context and text.

• Korean Journal of Cognitive Science
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• v.19 no.4
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• pp.459-476
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• 2008

The user needs to find the answer to your question is growing fast at the service using collective intelligent knowledge. In the previous researches, it was proven that the non-text information like view counting, referrer number, and number of answer is good in evaluating answers. There were also many works about evaluating answers using the various kinds of word dictionaries. In this work, we propose new method to evaluate answers to question effectively using user reputation that estimated by the social activity. We use a modified PageRank algorithm for estimating user reputation. We also use the similarity between question and answer. From the result of experiment in the Naver GisikiN corpus, we can see that the proposed method gives meaningful performance to complement the answer selection rate.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.1-10
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• 2006

In document clustering methods, the k-means algorithm and the Hierarchical Alglomerative Clustering(HAC) are often used. The k-means algorithm has the advantage of a processing time and HAC has also the advantage of a precision of classification. But both methods have mutual drawbacks, a slow processing time and a low quality of classification for the k-means algorithm and the HAC, respectively. Also both methods have the serious problem which is to compute a document similarity whenever new document is inserted into a cluster. A main property of web resource is to accumulate an information by adding new documents frequently. Therefore, we propose a new method of transitive closure tree based on the HAC method which can improve a processing time for a document clustering, and also propose a superior incremental clustering method for an insertion of a new document and a deletion of a document contained in a cluster. The proposed method is compared with those existing algorithms on the basis of a pre챠sion, a recall, a F-Measure, and a processing time and we present the experimental results.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.57-66
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• 2003

With the development of the internet and computer, the amount of information through the internet is increasing rapidly and it is managed in document form. For this reason, the research into the method to manage for a large amount of document in an effective way is necessary. The document clustering is integrated documents to subject by classifying a set of documents through their similarity among them. Accordingly, the document clustering can be used in exploring and searching a document and it can increased accuracy of search. This paper proposes an efficient incremental cluttering method for a set of documents increase gradually. The incremental document clustering algorithm assigns a set of new documents to the legacy clusters which have been identified in advance. In addition, to improve the correctness of the clustering, removing the stop words can be proposed and the weight of the word can be calculated by the proposed TF$\times$NIDF function.