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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Internet Computing and Services
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Korean Society for Internet Information
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Volume & Issues
Volume 15, Issue 6 - Dec 2014
Volume 15, Issue 5 - Oct 2014
Volume 15, Issue 4 - Aug 2014
Volume 15, Issue 3 - Jun 2014
Volume 15, Issue 2 - Apr 2014
Volume 15, Issue 1 - Feb 2014
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A video transmission system for a high quality and fault tolerance based on multiple paths using TCP/IP
Kim, Nam-Su ; Lee, Jong-Yeol ; Pyun, Kihyun ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 1~8
DOI : 10.7472/jksii.2014.15.6.01
As the e-learning spreads widely and demands on the internet video service, transmitting video data for many users over the Internet becomes popular. To satisfy this needs, the traditional approach uses a tree structure that uses the video server as the root node. However, this approach has the danger of stopping the video service even when one of the nodes along the path has a some problem. In this paper, we propose a video-on-demand service that uses multiple paths. We add new paths for backup and speed up for transmitting the video data. We show by simulation experiments that our approach provides a high-quality of video service.
AMV: A k-anonymization technique minimizing the cloaking region
Song, Doohee ; Heo, Minjae ; Sim, Jongwon ; Hwang, Sori ; Song, Moonbae ; Park, Kwangjin ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 9~14
DOI : 10.7472/jksii.2014.15.6.09
In this paper, we propose AMV scheme which supports k-anonymization by using vectors for mobile clients. AMV can produces the minimal cloaking area using motion vector information of users (clients). The main reason for minimizing cloaking area is a server has to send the object information to all users who request the spatial queries. The experimental results show that the proposed AMV has superior performance over existing methods.
A Study On The Economic Value Of Firm's Big Data Technologies Introduction Using Real Option Approach - Based On YUYU Pharmaceuticals Case -
Jang, Hyuk Soo ; Lee, Bong Gyou ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 15~26
DOI : 10.7472/jksii.2014.15.6.15
This study focus on a economic value of the Big Data technologies by real options model using big data technology company's stock price to determine the price of the economic value of incremental assessed value. For estimating stochastic process of company's stock price by big data technology to extract the incremental shares, Generalized Moments Method (GMM) are used. Option value for Black-Scholes partial differential equation was derived, in which finite difference numerical methods to obtain the Big Data technology was introduced to estimate the economic value. As a result, a option value of big data technology investment is 38.5 billion under assumption which investment cost is 50 million won and time value is a about 1 million, respectively. Thus, introduction of big data technology to create a substantial effect on corporate profits, is valuable and there are an effects on the additional time value. Sensitivity analysis of lower underlying asset value appear decreased options value and the lower investment cost showed increased options value. A volatility are not sensitive on the option value due to the big data technological characteristics which are low stock volatility and introduction periods.
The Loss Prevention System of Smart Device Using by iBeacon
Nam, ChoonSung ; Jung, HyunHee ; Shin, DongRyeol ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 27~34
DOI : 10.7472/jksii.2014.15.6.27
Todays, the rapid technical progress of smart device has been used for various social (wall-fare) services in our lives. Especially, most of these services are based on the Local-based Services (LBS) and this technology is getting popular more and more compared with before. Basically, LBS is able to support various types of geographical services such as vehicles' navigation services, Augmented reality services as using extensional local information such as GPS. However, LBS has serious mathematical vulnerability on the services frequently because of its miscalculated GPS data under interior and ambiguous geographical environment such like shadowed area. So, to overcome this limitation, iBeacon, which would be able to mitigate LBS miscalculation process, has been proposed recently among network experts. Compared with other wireless technologies, iBeacon is able to determine the accurate geographical data of certain local positions easily because it is not only designed based on low-powered data transmitting technology, but also, it can be much easy to be deployed. As users' dependency of smart devices are getting higher and higher and the use of smart device is also getting complex more and more, the users prefer to use various types of smart devices at one time. Therefore, in this paper, we propose the loss prevention system that is able to interwork smart devices networks as using iBeacon technology for users' better conveniences.
Development of The Korean Trust Index for Social Network Services
Kim, Yukyong ; Jhee, Eun-Wha ; Shin, Yongtae ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 35~45
DOI : 10.7472/jksii.2014.15.6.35
Due to the spread of unreliable online information on the social network services, the users are faced with a difficult problem for determining if the information is trustworthy or not. At present, the users should make a decision by themselves throughly for the trustworthiness of the information. Therefore, we need a way to systematically evaluate the trustworthiness of information on the social network services. In this paper, we design a trust index, called KTI (Korean Trust Index for SNS), as a criterion for measuring the trust degree of the information on the social network services. Using KTI, the users are readily able to determine whether the information is trustworthy. Consequently, we can estimate the social trust degree based on the variation of KTI. This paper derives the various factors affecting trust from the properties of the social network services, and proposes a model to evaluate the trustworthiness of information that is directly produced and distributed over the online network. Quantifying the trust degree of the information on the social network services allows the users to make efficient use of the social network.
An automatic detection scheme of anti-debugging routines to the environment for analysis
Park, Jin-Woo ; Park, Yong-Su ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 47~54
DOI : 10.7472/jksii.2014.15.6.47
Anti-debugging is one of the techniques implemented within the computer code to hinder attempts at reverse engineering so that attackers or analyzers will not be able to use debuggers to analyze the program. The technique has been applied to various programs and is still commonly used in order to prevent malware or malicious code attacks or to protect the programs from being analyzed. In this paper, we will suggest an automatic detection scheme for anti-debugging routines. With respect to the automatic detection, debuggers and a simulator were used by which trace information on the Application Program Interface(API) as well as executive instructions were extracted. Subsequently, the extracted instructions were examined and compared so as to detect points automatically where suspicious activity was captured as anti-debugging routines. Based on experiments to detect anti-debugging routines using such methods, 21 out of 25 anti-debugging techniques introduced in this paper appear to be able to detect anti-debugging routines properly. The technique in the paper is therefore not dependent upon a certain anti-debugging method. As such, the detection technique is expected to also be available for anti-debugging techniques that will be developed or discovered in the future.
OTACUS: Parameter-Tampering Prevention Techniques using Clean URL
Kim, Guiseok ; Kim, Seungjoo ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 55~64
DOI : 10.7472/jksii.2014.15.6.55
In a Web application, you can pass without restrictions special network security devices such as IPS and F/W, URL parameter, which is an important element of communication between the client and the server, is forwarded to the Web server. Parameters are modulated by an attacker requests a URL, disclose confidential information or through e-commerce, can take financial gain. Vulnerability parameter manipulation thereof cannot be able to determine whether to operate in only determined logical application, blocked with Web Application Firewall. In this paper, I will present a technique OTACUS(One-Time Access Control URL System) to complement the shortcomings of the measures existing approaches. OTACUS can be effectively blocked the modulation of the POST or GET method parameters passed to the server by preventing the exposure of the URL to the attacker by using clean URL technique simplifies complex URL that contains the parameter. Performance test results of the actual implementation OTACUS proves that it is possible to show a stable operation of less than 3% increase in the load.
Trend Analysis using Spatial-Temporal Visualization of Event Information based on Social Media
Oh, Hyo-Jung ; Yun, Bo-Hyun ; Yoo, Cheol-Jung ; Kim, Yong ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 65~75
DOI : 10.7472/jksii.2014.15.6.65
The main focus of this paper is to analyze trend of event informations in a variety of mass media by graphical visualization in axis of the time and location. Especially, continuity analysis based on user-generated social media can reflect the social impact of a certain event according to change time and location and their directional changes. To reveal the characteristics of continuous events, we survey the data set collected from news articles and tweets during two years. Based on case studies on 'disease' and 'leisure', we verify the effectiveness and usefulness of our proposed method. Even though some events occurred during same period, we showed directional changes which have high-impact in social media referred user interest's, compared with fact-based continuous visualization results.
A Study on the Structural Equation Modeling for the effect of e-Learning
Heo, Gyun ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 77~84
DOI : 10.7472/jksii.2014.15.6.77
The purpose of this study is to explore factors affecting the effect of e-learning, and to find out the casual relationship among these factors. Subjects are 2,091 students who have participated in e-learning based class during the period of second semester in 2013. Those of them, 1,732 students response to the survey questions. After gathering data, they are analyzed by using Confirmative Factor Analysis and Structural Equation Modeling. From the result of Confirmative Factor analysis, data have reduced four factors, and are named as four latent variables likes e-learning effect, contents satisfaction, managing assistant factor, and system functional factor. From the result of Structural Equation Modeling, it is known as the relation and impact among factors: (a) "managing assistant factor" affects to "contents satisfaction" directly. (b) "contents satisfaction" affects to "e-learning effect" directly. (c) "system function factor" affects directly to "contents satisfaction", but does not affect directly to "e-learning effect". (d) both "managing assistant factor" and "system function factor" have an indirect effect on "e-learning effect" via "contents satisfaction".
A Method for Dynamic Clustering-based Efficient Management in Large-Scale IoT Environment
Kim, Dae Young ; La, Hyun Jung ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 85~97
DOI : 10.7472/jksii.2014.15.6.85
IoT devices that collect information for end users and provide various services like giving traffic or weather information to them that are located everywhere aim to raise quality of life. Currently, the number of devices has dramatically increased so that there are many companies and laboratories for developing various IoT devices in the world. However, research about IoT computing such as connecting IoT devices or management is at an early stage. A server node that manages lots of IoT device in IoT computing environment is certainly needed. But, it is difficult to manage lots of devices efficiently. However, anyone cannot surly know about how many servers are needed or where they are located in the environment. In this paper, we suggest a method that is a way to dynamic clustering IoT computing environment by logical distance among devices. With our proposed method, we can ensure to manage the quality in large-scale IoT environment efficiently.
A study on integrating and discovery of semantic based knowledge model
Chun, Seung-Su ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 99~106
DOI : 10.7472/jksii.2014.15.6.99
Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.
A Design and Development of Big Data Indexing and Search System using Lucene
Kim, DongMin ; Choi, JinWoo ; Woo, ChongWoo ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 107~115
DOI : 10.7472/jksii.2014.15.6.107
Recently, increased use of the internet resulted in generation of large and diverse types of data due to increased use of social media, expansion of a convergence of among industries, use of the various smart device. We are facing difficulties to manage and analyze the data using previous data processing techniques since the volume of the data is huge, form of the data varies and evolves rapidly. In other words, we need to study a new approach to solve such problems. Many approaches are being studied on this issue, and we are describing an effective design and development to build indexing engine of big data platform. Our goal is to build a system that could effectively manage for huge data set which exceeds previous data processing range, and that could reduce data analysis time. We used large SNMP log data for an experiment, and tried to reduce data analysis time through the fast indexing and searching approach. Also, we expect our approach could help analyzing the user data through visualization of the analyzed data expression.
Context Aware Feature Selection Model for Salient Feature Detection from Mobile Video Devices
Lee, Jaeho ; Shin, Hyunkyung ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 117~124
DOI : 10.7472/jksii.2014.15.6.117
Cluttered background is a major obstacle in developing salient object detection and tracking system for mobile device captured natural scene video frames. In this paper we propose a context aware feature vector selection model to provide an efficient noise filtering by machine learning based classifiers. Since the context awareness for feature selection is achieved by searching nearest neighborhoods, known as NP hard problem, we apply a fast approximation method with complexity analysis in details. Separability enhancement in feature vector space by adding the context aware feature subsets is studied rigorously using principal component analysis (PCA). Overall performance enhancement is quantified by the statistical measures in terms of the various machine learning models including MLP, SVM, Naïve Bayesian, CART. Summary of computational costs and performance enhancement is also presented.
A Weighted Frequent Graph Pattern Mining Approach considering Length-Decreasing Support Constraints
Yun, Unil ; Lee, Gangin ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 125~132
DOI : 10.7472/jksii.2014.15.6.125
Since frequent pattern mining was proposed in order to search for hidden, useful pattern information from large-scale databases, various types of mining approaches and applications have been researched. Especially, frequent graph pattern mining was suggested to effectively deal with recent data that have been complicated continually, and a variety of efficient graph mining algorithms have been studied. Graph patterns obtained from graph databases have their own importance and characteristics different from one another according to the elements composing them and their lengths. However, traditional frequent graph pattern mining approaches have the limitations that do not consider such problems. That is, the existing methods consider only one minimum support threshold regardless of the lengths of graph patterns extracted from their mining operations and do not use any of the patterns' weight factors; therefore, a large number of actually useless graph patterns may be generated. Small graph patterns with a few vertices and edges tend to be interesting when their weighted supports are relatively high, while large ones with many elements can be useful even if their weighted supports are relatively low. For this reason, we propose a weight-based frequent graph pattern mining algorithm considering length-decreasing support constraints. Comprehensive experimental results provided in this paper show that the proposed method guarantees more outstanding performance compared to a state-of-the-art graph mining algorithm in terms of pattern generation, runtime, and memory usage.
Effects of Purchasing Factors through Social-commerce of Beauty Service on the Consumer Satisfaction and the Repurchasing Intention
Hong, Soo-Nam ; Lee, Han-Joo ;
Journal of Internet Computing and Services, volume 15, issue 6, 2014, Pages 133~144
DOI : 10.7472/jksii.2014.15.6.133
As the Internet and smartphones prevail, this study investigated the purchasing factors of a new beauty marketing method, the social commerce, and verified the relationship of such purchasing factors to consumer satisfaction and repurchasing intentions. In order to verify the validity of purchasing factors, five sub-factors, such as service, price, interaction, convenience, and interest were classified, while consumer satisfaction and repurchasing intentions are grouped into one factor, using data about 20-39 years old. According to results of this study, purchasing factors in the beauty service markets through social commerce that had effects on the consumer satisfaction were price, service, convenience, and interest, but no relationship was found with interaction. We can predict that consumers buy not based on community activities among buyers or purchasing comments of others, but rather his/her own subjective thoughts and opinions about the services. As the result of repurchasing intention according to purchasing factors, affecting sub-factors were price, service, and convenience. Repurchasing intention is an positive response that reflects satisfactions. Since low price, satisfaction on the service, and convenience for busy modern people should be met, repurchasing intentions are not affected by interest, but rather systematic and professional service. Also, higher satisfaction on service raises repurchasing intention. In this study, it is clear that not only purchasing factors through social-commerce effect the satisfaction and the repurchasing intention, but also consumer satisfaction mediates partly purchasing factors and the repurchasing intention. And as sub-factors of purchasing factors, price, service, or convenience are more important to the consumer satisfaction than community or replies activities. Thus differentiated and professional customer service, the establishment and enhancement of trendy marketing should improve long term repurchasing intentions. This will lead to the increasing revenue of personal-shop and the developments of beauty markets, so strengthening product sourcing and promotion suitable for mobile shoppers are essential.