• Journal of Digital Contents Society
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• v.18 no.5
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• pp.821-829
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• 2017

In recent, there has been a great change in the shopping market due to the development of the Internet and the generalization of mobile devices. Customers have become more comfortable with online shopping where they can purchase clothes without having to visit their own shop directly. While online shopping is convenient and easy to buy, it is difficult to judge whether it is suitable for you to buy clothes. This paper proposes an application that users virtually coordinate on their own full-body photo or a user-specified model. The proposed application encourages smart purchases by enabling users to see their virtual coordination on their bodies.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1109-1116
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• 2018

The purpose of this study is to solve the loss of personal belongings by utilizing monitoring function of IoT platform. The beacon to combined with personal belongings are registered with the application server, the trigger processing function according to the occurrence of the lost event is performed intelligently through the device, the app, the IoT network, and the application server.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1457-1465
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• 2017

With the growing of smart devices market, malicious behavior has gradually expanded its scope. Accordingly, many studies have been conducted to analyze malicious apps and automated analysis tools have been released. However these tools cause the side effects that the application protection tools such as ProGuard, DexGuard become vulnerable to analyzers or attackers. This paper suggests the protection mechanism to apply to the Android apps using security token, rather than general-purpose protection solutions that can be applied in malicious apps. The main features of this technique are that Android app is not properly loaded in the memory when the security token is abnormal or is not inserted and protected parts using the technique are not exposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.367-369
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• 2017

Recently, many crimes are occurred frequently on the public roads. The purpose of this application is to inform people who are in need of safety about places where they can be protected from the dangerous situations and help them to be prepared for the risks. It is a key feature of this application to show the locations of CCTV, police station, and guard houses, etc. when the user is in the potential danger.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.195-203
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• 2019

Mobile applications stores such as Google Play Store and Apple App Store, are widely used to distribute a variety of applications including finance, shopping, and entertainment. Recently, however, vulnerabilities of the mobile applications are likely to violate users' privacy such as personal information leakage. In this paper, we classify mobile applications that can be download from mobile stores, and analyze the personal information that could be leaked when users are using the mobile applications. As a result of analysis, we found that personal information are leaked in some widely used mobile applications in practice. On the basis of our experiment results, we propose some mitigations to enhance security of the mobile applications and prevent leakage of personal information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.457-460
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• 2014

As to the rapid development of mobile technology, the era of 1-person 1-smart phone has come. Also, the application of smart phone became the part of our life. Especially mobile RPG(Role Playing Game) has the biggest market and the largest number of users. There could be no precise quality assessment result, if quality evaluation model of PC RPG game were applied to the mobile RPG. Thus, it is time to focus on new quality evaluation model for mobile RPG with the great reflection of smart phone attributes. In this paper, based on ISO/IEC 9126, the international standard of software quality, quality evaluation elements for mobile RPG were deducted. Then metrics for validation of elements were redefined and new quality evaluation model was proposed.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.750-759
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• 2020

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

• Journal of Fashion Business
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• v.19 no.6
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• pp.82-100
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• 2015

Mobile fashion apps present much opportunity for marketers to engage consumers, however not all apps provide enough functions for their targeted audience. This study aims to determine how mobile fashion apps can be used to build brand community with consumer engagement. Qualitative data on fashion mobile apps were collected from the Apple app store and Android market during the spring and summer of 2015. A total of 110 fashion mobile apps were collected;, 50 apps were identified as apparel brands that either manufacture or sell apparel to consumers, which we categorized as "brand" fashion apps, and the remaining 60 were categorized as "non-brand" fashion apps. The result of the study can be summarized as below. The 60 non-brand fashion apps were grouped into 5 app types: shopping, searching, sharing, organizational, and informational. The main functions are for informational use and shopping needs, since at least half (31 apps) are used for either retrieving information or for shopping. However, in contrast, social networking and location were infrequent and not commonly utilized by these apps. The most common type of non-brand fashion apps available were shopping apps;, many shopping apps enable users to shop from several different websites and save their items into one universal shopping cart so that they only check out once. Most of these apps are informational and help consumers make more informed decisions on purchases;, in addition many offer location services to help consumers find these items in store. While these apps perform several functions, they do not link to social media. The 50 brand apps were grouped into 5 brand types: athletic, casual, fast fashion, luxury, and retailer. These apps were also checked for attributes to determine their functionality. The result shows that the main functions of brand fashion apps are for information (82% of the 50 apps) as well as location searching (72% of 50 apps). Conversely, these apps do not offer any photo sharing, and very few have organizational or community functions. Fashion mobile apps and m-marketing elements: To build brand community, mobile apps can be designed to motivate consumer's engagement with brands. The motivations of fashion mobile apps are useful in developing fashion mobile apps. Entertainment motives can be fulfilled with multimedia attributes, functionality motives are satisfied with organizational and location-based features, information motives with informational service, socialization with community and social network, learning and intellectual stimulation from informational attributes, and trend following through photo sharing. The 8 key attributes of mobile apps can correspond to the 4 m-marketing elements (i.e., Informative content, multimedia, interactions, and product promotions) that are further intertwined with m-branding elements. App Attributes and M-Marketing aim to Build Brand Community;, the eight key attributes can impact on 4 m-branding elements, which further contribute to building brand community by affecting consumers' perceptions of brands preference and advocacy, and their likelihood to be loyal.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.657-667
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• 2020

The Android framework allows apps to take full advantage of personal information through granting single permission, and does not determine whether the data being leaked is actual personal information. To solve these problems, we propose a tool with static/dynamic analysis. The tool analyzes the Source and Sink used by the target app, to provide users with information on what personal information it used. To achieve this, we extracted the Source and Sink through Control Flow Graph and make sure that it leaks the user's privacy when there is a Source-to-Sink flow. We also used the sensitive permission information provided by Google to obtain information from the sensitive API corresponding to Source and Sink. Finally, our dynamic analysis tool runs the app and hooks information from each sensitive API. In the hooked data, we got information about whether user's personal information is leaked through this app, and delivered to user. In this process, an automated Source/Sink classification model was applied to collect latest Source/Sink information, and the we categorized latest release version of Android(9.0) with 88.5% accuracy. We evaluated our tool on 2,802 APKs, and found 850 APKs that leak personal information.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.239-247
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• 2013

This study is aimed to perform the qualitative evaluation based on the ARCS Model of educational mobile applications for smart phones. The evaluation has been performed targeting 60 students who attending the subject of informational education in 3 different universities in 2012 by allowing them to select the available educational mobile App installed in their smart phone. After, the level of persistent learning-intension from each student and the efficacy of ARCS motivational strategy was measured at learner's perspective. The structural equation model(SEM) was established and analyzed with PLS method to understand the relationship between the ARCS motivational strategy and the persistent learning-intension. The results of the study could be summarized as followings. First, the educational mobile App in various the motivational strategies showed different results that is the highest attention as well as the lowest satisfactory level. Second, the relevance in motivation strategies had the statistically significant effect in attention, confidence, and satisfaction. On the other hand, the other factors of attention, relevance, and confidence showed statistically significant effect in satisfaction. Finally, result demonstrate that the relevance is the critical factor inducing the significant effect in persistent learning-intension among the motivational strategies.