• International Journal of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.11-18
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• 2016

Due to open source policy, Android systems are exposed to a variety of security problems. In particular, app reuse attacks are detrimental threat to the Android system security. This is because attacker can create core malign components and quickly generate a bunch of malicious apps by reusing these components. Hence, it is very imperative to discern whether Android apps contain reused components. To meet this need, we propose an Android app reuse analysis technique based on the Sequential Hypothesis Testing. This technique quickly makes a decision with a few number of samples whether a set of Android apps is made through app reuse. We performed experimental study with 6 malicious app groups, 1 google and 1 third-party app group such that each group consists of 100 Android apps. Experimental results demonstrate that our proposed analysis technique efficiently judges Android app groups with reused components.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.267-270
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• 2021

현재 세계 모바일 App 시장에서는 메신저 서비스가 꾸준히 인기를 이어가고 있으며 국내 모바일 메신저 시장 또한 월간이용자수가 꾸준히 유지되고 있다. 이에 따라 많은 App들이 메신저 기능을 제공하기 위해 자체 채팅 서비스를 도입하거나 외부 메신저 App을 연동하는 방법을 사용하고 있다. 하지만 중·소 IT 기업의 경우 자체 개발 인력 및 인프라를 마련하는데 한계가 있으며 외부 메신저 App 연동 시 이탈 역효과의 단점이 발생한다. 이에 본 논문은 중·소 IT 기업에 활용성을 높일 수 있는 STOMP 프로토콜 활용 자체 메신저 App 서비스를 개발하려 한다. 본 논문을 통해 App 자체에서 메신저 기능을 손쉽게 도입해 이용자 이탈율 최소화를 기대한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.576-577
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• 2021

In this paper, we describe the learning and quiz app using the app inventor and conducted the related questionnaire. We developed a learning philosophy for preliminary early childhood teachers using the developed apps and taught them how to utilize them in early childhood education by explaining the apps and using the app inventor. Through questionnaires, we confirmed the learning effect and the willingness to use in early childhood education. Through this study, I hope to improve the ability of early childhood teacher learning and to utilize the coding in early childhood education with the app developed as the app inventor.

• Information Systems Review
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• v.18 no.1
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• pp.125-140
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• 2016

Mobile applications (apps) play a significant role in the proliferation of smartphones. According to statistics from Apple, 100 million apps were downloaded in 2008. Since then, the number of cumulative app downloads have increased exponentially. By October 2014, 85 billion apps had been downloaded worldwide. Many studies have attempted to determine the factors that drive app downloads. However, unlike previous studies, we examine the effects of app updates on app rankings. To achieve this goal, we collected data on rankings (gross rankings and category rankings), update contents, reviewer ratings, and number of reviews on apps listed in the App Store. We then categorized app updates into functionality, reliability, and convenience updates following the buying hierarchy model. We found that functionality updates had a positive effect on app gross ranking whereas reliability updates had a positive effect on category ranking. Our study is the first to explore the effects of update content on app ranking. Moreover, our study provides a practical implication for mobile app developers, who should consider app updates in their product development strategy.

• The Journal of Korean Association of Computer Education
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• v.19 no.6
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• pp.25-32
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• 2016

This study aims to suggest app programming education plan by analyzing the effects of app programming education using m-bizmaker on the creative problem solving ability in specialized high school students. Currently, The South Korean government is preparing to conduct SW education in primary and secondary schools. Developing smartphone apps that are familiar to students can be seen as a very effective tool of SW educational measures. In general, app development can only be achieved through specialized training on how to use the app programming language. So, many students think the app programming is difficult areas before creating apps because tired of learning how to an app programming language. As a result of applying app programming education using m-Bizmaker, which is one of the app authoring tools, to the class, it is desirable as an app programming education plan. And according to survey results, it has been proved that the app programming education plan using m-Bizmaker is effective to improve creative problem solving ability.

• The Korean Journal of Physiology and Pharmacology
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• v.14 no.4
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• pp.229-233
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• 2010

Amyloid precursor protein binding protein-1 (APP-BP1) binds to the carboxyl terminus of amyloid precursor protein and serves as a bipartite activation enzyme for the ubiquitin-like protein, NEDD8. Previously, it has been reported that APP-BP1 rescues the cell cycle S-M checkpoint defect in Ts41 hamster cells, that this rescue is dependent on the interaction of APP-BP1 with hUba3. The exogenous expression of APP-BP1 in neurons has been reported to cause DNA synthesis and apoptosis via a signaling pathway that is dependent on APP-BP1 binding to APP. These results suggest that APP-BP1 overexpression contributes to neurodegeneration. In the present study, we explored whether APP-BP1 expression was altered in the brains of Tg2576 mice, which is an animal model of Alzheimer's disease. APP-BP1 was found to be up-regulated in the hippocampus and cortex of 12 month-old Tg2576 mice compared to age-matched wild-type mice. In addition, APP-BP1 knockdown by siRNA treatment reduced cullin-1 neddylation in fetal neural stem cells, suggesting that APP-BP1 plays a role in cell cycle progression in the cells. Collectively, these results suggest that increased expression of APP-BP1, which has a role in cell cycle progression in neuronal cells, contributes to the pathogenesis of Alzheimer's disease.

• Journal of Information Technology Services
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• v.14 no.3
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• pp.1-18
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• 2015

Recent trends of mobile convergence has already brought about many changes in our digitally-powered society. Especially, taking advantage of strengths of existing mobile devices and smart phones have already been established as a primary standard in the business intelligence world. Such high-powered digital devices equipped with mobile convergence functions are getting more momentum as app stores are prevailing. Basically, the app stores are administered by smart phone manufacturers, creating a new business ecosystem among app developers and end-users. However, there are paucity of studies tackling an issue about how users' repurchase intention of the apps is influenced by the service qualities of the app stores. In this respect, this study aims to investigate the effect of app store service quality on users' satisfaction and repurchase intention. As the value of loyal customers is incomparably high in app commerce, winning customers' loyalty is vital to the success of app stores. In this study, a customer is defined as one who has purchased goods or services at least once from the app stores. The proposed research model includes a number of constructs such as app perceptions, customer service, perceived ease of use, design, promotion, perceived consumer risk and connectivity. Empirical results revealed that perceived consumer risk has a negative relationship with consumer's perceived repurchase intention. All the other variables-app perceptions, customer service, perceived ease of use, design, promotion, connectivity- are found to be positively related with the repurchase intentions.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.111-116
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• 2014

Thanks to diffusions of mobile devices and advances of network technologies, demands for mobile app have been increased dramatically. It has resulted in mobile app industries as well as mobile app authoring tools are facing a crisis over subordinate to specific OS and platform such as iOS, Android and Apple App Store. Because these particular OS and platforms are obstacles to overcome for supporting interoperability and compatibility. In this study, we have conducted expert interviews and surveys to analyze status of mobile app markets and needs for mobile app user and developer. As a result, mobile app based on HTML5 leads to interconnect various mobile devises without additional efforts. Thereby, mobile app user and developer take a positive view of HTML5. However, mobile app developers tend to have the technical path dependence, they especially in venture and small enterprises need to government support for professional manpower training.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.58-73
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• 2022

The purpose of this study is to construct a predictable estimation model that reflects the relationship between the variables of mobile app performance and to verify how app reviews affect app performance. In study 1 and 2, the relationship between app performance indicators was derived using correlation analysis and random forest regression estimation of machine learning, and app performance estimation modeling was performed. In study 3, sentiment scores for app reviews were by using sentiment analysis of text mining, and it was found that app review sentiment scores have an effect one lag ahead of the number of daily installations of apps when using multivariate time series analysis. By analyzing the dissatisfaction and needs raised by app performance indicators and reviews of apps, companies can improve their apps in a timely manner and derive the timing and direction of marketing promotions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.455-457
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• 2021

App is used on mobile devices such as smartphones and also has malicious code, which can be divided into normal and malicious depending on the presence or absence of hacking codes. Because there are many kind of malware, it is difficult to detect directly, we propose a method to detect malicious app using AI. Most of the existing methods are to detect malicious app by extracting features from malicious app. However, the number of types have increased exponentially, making it impossible to detect malicious code. Therefore, we would like to propose two more methods besides detecting malicious app by extracting features from most existing malicious app. The first method is to learn normal app to extract normal's features, as opposed to the existing method of learning malicious app and find abnormalities (malicious app). The second one is an 'ensemble technique' that combines the existing method with the first proposal. These two methods need to be studied so that they can be used in future mobile environment.