• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.55-66
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• 2016

A local storage of HTML5 is a Web Storage, which is stored permanently on a local computer in the form of files. The contents of the storage can be easily accessed and modified because it is stored as plaintext. Moreover, because the internet browser classifies the local storages of each domain using file names, the malicious attacker can abuse victim's local storage files by changing file names. In the paper, we propose a scheme to maintain the integrity and the confidentiality of the local storage's source domain and source device. The key idea is that the client encrypts the data stored in the local storage with cipher key, which is managed by the web server. On the step of requesting the cipher key, the web server authenticates whether the client is legal source of local storage or not. Finally, we showed that our method can detect an abnormal access to the local storage through experiments according to the proposed method.

• The Journal of Korean Academic Society of Nursing Education
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• v.17 no.3
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• pp.424-432
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• 2011

Purpose: This study was done to investigate the current conditions with communication-related education in the nursing undergraduate curriculum, and to develop effective strategies for communication education. Methods: We collected 48 syllabi of communication-related courses from the nursing college or nursing department of a university and analyzed the syllabi using the content analysis method. Results: First, in the knowledge domain, 'Theories of communication', 'Characteristics of human relationship, understanding the importance, and building philosophical foundations' were covered. Second, the skill domain covered 'Application of communication for nursing care' as a main concept. Third, 'Building human relationships for nursing care' was mainly covered in the attitude domain. On the other hand, topics and content were different depending on instructors. Although the courses covered the same educational content, they were categorized under different names and concepts. Conclusion: These findings have implications for how to standardize a communication course in the nursing curriculum.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1126-1132
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• 2012

To enhance network efficiency, CCN allow intermediate network nodes between a content consumer and a content publisher to temporarily cache transmitted contents. Then the network nodes immediately return back the cached contents to another consumers when the nodes receives relevant contents request messages from the consumers. For that, CCN utilizes hierarchical content names to forward a request message as well as a response message. However, such content names semantically contain much information about domain/user as well as content itself. So it is possible to invade users' privacy. In this paper, we first review both the problem of CCN name in the view point of privacy and proposed schemes. Then we propose an improved name management scheme for users' privacy preservation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.3
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• pp.560-574
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• 2011

In this paper, we propose a hybrid method of Machine Learning (ML) algorithm and a rule-based algorithm to implement a lightweight Named Entity (NE) extraction system for Korean SMS text. NE extraction from Korean SMS text is a challenging theme due to the resource limitation on a mobile phone, corruptions in input text, need for extension to include personal information stored in a mobile phone, and sparsity of training data. The proposed hybrid method retaining the advantages of statistical ML and rule-based algorithms provides fully-automated procedures for the combination of ML approaches and their correction rules using a threshold-based soft decision function. The proposed method is applied to Korean SMS texts to extract person's names as well as location names which are key information in personal appointment management system. Our proposed system achieved 80.53% in F-measure in this domain, superior to those of the conventional ML approaches.

• Journal of Korean Library and Information Science Society
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• v.47 no.4
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• pp.289-307
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• 2016

This paper introduces a software system and process model for constructing domain-specific relation extraction datasets semi-automatically. The system uses a set of terms such as genes, proteins diseases and so forth as inputs and then by exploiting massive biological interaction database, generates a set of term pairs which are utilized as queries for retrieving sentences containing the pairs from scientific databases. To assess the usefulness of the proposed system, this paper applies it into constructing a genic interaction dataset related to Alzheimer's disease domain, which extracts 3,510 interaction-related sentences by using 140 gene names in the area. In conclusion, the resulting outputs of the case study performed in this paper indicate the fact that the system and process could highly boost the efficiency of the dataset construction in various subfields of biomedical research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2750-2763
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• 2012

The Domain Name System (DNS) is a critical Internet infrastructure that provides name to address mapping services. In the past decade, Denial-of-Service (DoS) attacks have targeted the DNS infrastructure and threaten to disrupt this critical service. While the flooding DoS attacks may be alleviated by the DNS caching mechanism, we show in this paper that flooding DoS attacks utilizing name error queries is capable of bypassing the cache of resolvers and thereby impose overwhelming flooding attacks on the name servers. We analyze the impacts of such DoS attacks on both name servers and resolvers, which are further illustrated by May 19 China's DNS Collapse. We also propose the detection and defense approaches for protecting DNS servers from such DoS attacks. In the proposal, the victim zones and attacking clients are detected through monitoring the number of corresponding responses maintained in the negative cache. And the attacking queries can be mitigated by the resolvers with a sample proportion adaptive to the percent of queries for the existent domain names. We assess risks of the DoS attacks by experimental results. Measurements on the request rate of DNS name server show that this kind of attacks poses a substantial threat to the current DNS service.

• Journal of Information Science Theory and Practice
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• v.3 no.1
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• pp.6-23
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• 2015

This study develops an effective method for sentiment analysis of user-generated content on drug review websites, which has not been investigated extensively compared to other general domains, such as product reviews. A clause-level sentiment analysis algorithm is developed since each sentence can contain multiple clauses discussing multiple aspects of a drug. The method adopts a pure linguistic approach of computing the sentiment orientation (positive, negative, or neutral) of a clause from the prior sentiment scores assigned to words, taking into consideration the grammatical relations and semantic annotation (such as disorder terms) of words in the clause. Experiment results with 2,700 clauses show the effectiveness of the proposed approach, and it performed significantly better than the baseline approaches using a machine learning approach. Various challenging issues were identified and discussed through error analysis. The application of the proposed sentiment analysis approach will be useful not only for patients, but also for drug makers and clinicians to obtain valuable summaries of public opinion. Since sentiment analysis is domain specific, domain knowledge in drug reviews is incorporated into the sentiment analysis algorithm to provide more accurate analysis. In particular, MetaMap is used to map various health and medical terms (such as disease and drug names) to semantic types in the Unified Medical Language System (UMLS) Semantic Network.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.36-46
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• 2019

The number of hosts connected to the Internet has increased dramatically, introducing the Domain Name System(DNS) in 1984. DNS is now an important key point for all users of the Internet by allowing them to use a convenient character address without memorizing a series of numbers of complex IP address. However, relative to the importance of DNS, there still exist many problems such as the authorization allocation issue, the disputes over public registration, security vulnerability such as DNS cache poisoning, DNS spoofing, man-in-the-middle attack, DNS amplification attack, and the need for many domain names in the age of hyper-connected networks. In this paper, to effectively improve these problems of existing DNS, we proposed a method of implementing DNS using distributed ledger technology, blockchain, and implemented using a Ethereum-based platform. In addition, the qualitative analysis performance comparative evaluation of the existing domain name registration and domain name server was conducted, and conducted security assessments on the proposed system to improve security problem of existing DNS. In conclusion, it was shown that DNS services could be provided high security and high efficiently using blockchain.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.6 s.154
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• pp.928-938
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• 2006

Tween refers 'between' generation aged of 10-16 who are between child and high teens. Tweens have been regarded as one of the fast growing markets and they show some unique characteristics as next-generation consumers. This study has explored the perception of their appearances and clothing styles, style preferences, and influencing factors on clothing behavior of tweens. 120 students aged of 12-15 participated in depth interview and data were structured and categorized by applying domain analysis. Results showed tweens have great concerns on their appearances and styles, so they want to express their identities and aesthetic favors through clothing styles. As for clothing style preferences, they have multi-facet tastes such as casual, active, feminine/ masculine, sophisticated, dramatic, etc. Factors influencing on their clothing behavior include reference groups like friends, dual desires of conformity and individuality, fashion, and brand names.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.12
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• pp.1933-1939
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• 1990

In this paper, we proposed an algorithm which used backtracking method to get time information, and it be modelled DMS (Dynamic Multisection) by feature vectors and time information whic are represented to similiar feature in word patterns spoken during continuous time domain, for Korean Speech recognition by independent speaker using DMS. Each state of model is represented time sequence, and have time information and feature vector. Typical feature vector is determined as the feature vector of each state to minimize the distance between word patterns. DDD Area names are selected as recognition wcabulary and 12th LPC cepstrum coefficients are used as the feature parameter. State of model is made 8 multisection and is used 0.2 as weight for time information. Through the experiment result, recognition rate by DMS model is 94.8%, and it is shown that this is better than recognition rate (89.3%) by MSVQ(Multisection Vector Quantization) method.