• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.403-412
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• 2021

As the number of mobile apps increases exponentially, automation of tests performed in the app development process is becoming more important. Until the app is released, iterative verification is performed through various types of tests, and this study was conducted focusing on the GUI test among various types of tests. This study is meaningful in that it can contribute to the stable app distribution of the developer by suggesting the development direction of the GUI test. To develop Android's GUI test tool, I collected basic data before presenting the development method by researching Android's UI controls and Material design guideline. After that, for the existing GUI test automation tool, two tools based on screen capture test and four tools based on source code analysis test were studied. Through this, it was found that existing GUI test tools don't consider visual design, usability, and component arrangement. In order to supplement the shortcomings of existing tools, a new GUI test automation tool development method was presented based on the basic data previously studied.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.163-169
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• 2012

Since only one application has monopoly on LCD device of the mobile device in Android platform, the user can not see two screens together displayed by two applications running simultaneously. In this paper, a dual-app has been defined as two mobile applications running on each device of a pair of two mobile devices and DSAP or Dual Screen Android Platform has been implemented. DSAP does remote-execution of the peer application of a dual-app on the peer mobile device when either application of the dual-app starts to run and supports communication of the pair app over the network. This paper describes details of design and implementation of DSAP and shows a sample case utilizing DSAP.

• Journal of Digital Convergence
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• v.9 no.6
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• pp.343-354
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• 2011

The interactions between a professor and students are very important in humanities classes A professor could not exchange opinions with students especially in large-scale classes. We have developed a smart phone app. in order to overcome the lirnit of interaction between a professor and students in large-scale classes. The app we have developed in this paper have exploited smart phone's data processing and wireless communication ability. In this paper, we showed that smart phone could be an useful tool for increasing the education effect of large-scale classes.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.33-41
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• 2013

In this paper, we implemented the pattern matching with the Arduino and App Inventor platform under the bluetooth mobile environment between Android phone and Arduino Platform. The combination between Arduino and App Inventor makes the feasibility of Android programming easy by wireless communications and provides the opportunity to broaden the functionality for mobile device. We used the softwares which were Arduino IDE, VC++, OpenCV, Processing and App Inventor. And also compared the performance of mobile Arduino platform with LabView GUI programming, we reduced the usage of libraries that compiled and executed the pattern matching programming. We experimented the mobile embedded platform performance under bluetooth communication and verified the functionality of the mobile Arduino platform design for identifying the pattern matching.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.574-576
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• 2010

This paper describes constructing methods of environments for the App development using v smart-phones which are widespread rapidly. Various smart-phones and operating systems are used all over the world. In this paper, we will deal with three kinds of smart-phones, that is Windows Mobile Phone(recently Windows Phone7), iPhone and Android Phone using respective operating systems which are widespread in the domestic market.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.223-225
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• 2012

본 논문에서는 안드로이드 기반 스마트폰을 이용하여 유아 및 아동을 대상으로 하는 학습용 동화 앱의 구현 내용을 소개하였다. 이미 상용화 되어 있는 학습용 앱의 기능 외에 게임적 요소를 접목하여 학습의 효과와 흥미를 높일 수 있도록 하였다. 듣고 쓸 수 있는 학습용 전자 동화책으로 평가할 수 있다. 안드로이드 마켓에 배포하여 서비스를 할 수 있으며 본 연구의 과정은 앱 설계 관련 프로젝트의 수행이나 학습용 앱 개발의 학습 모형을 제시한 사례로 활용할 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1375-1380
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• 2021

Korea's security response to application service app is still insufficient due to the initial opening of the public safety network. Therefore, preemptive security measures are essential. In this study, we proposed to establish a 'public safety network app security system' to prevent potential vulnerabilities to the app store that distributes app in public safety network and android operating system that operate app on dedicated terminal devices. In order for an application service app to be listed on the public safety network mobile app store, a dataset of malicious and normal app is first established to extract characteristics and select the most effective AI model to perform static and dynamic analysis. According to the analysis results, 'Safety App Certificate' is certified for non-malicious app to secure reliability for listed apps. Ultimately, it minimizes the security blind spots of public safety network app. In addition, the safety of the network can be secured by supporting public safety application service of certified apps.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.125-139
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• 2013

Distribution of malicious applications developed by attackers is increasing along with general normal applications due to the openness of the Android-based open market. Mechanism that allows more accurate ways to distinguish normal apps and malicious apps for common mobile devices should be developed in order to reduce the damage caused by the rampant malicious applications. This paper analysed the normal event pattern from the most highly used game apps in the Android open market to analyse the event pattern from normal apps and malicious apps of mobile devices that are based on the Android platform, and analysed the malicious event pattern from the malicious apps and the disguising malicious apps in the form of a game app among 1260 malware samples distributed by Android MalGenome Project. As described, experiment that extracts normal app and malicious app events was performed using Strace, the Linux-based system call extraction tool, targeting normal apps and malicious apps on Android-based mobile devices. Relevance analysis for each event set was performed on collected events that occurred when normal apps and malicious apps were running. This paper successfully extracted event similarity through this process of analyzing the event occurrence characteristics, pattern and distribution on each set of normal apps and malicious apps, and lastly suggested a mechanism that determines whether any given app is malicious.

• Journal of KIISE
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• v.42 no.12
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• pp.1611-1622
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• 2015

Although Android systems provide a permission-based access control mechanism and demand a user to decide whether to install an app based on its permission list, many users tend to ignore this phase. Thus, an improved method is necessary for users to intuitively make informed decisions when installing a new app. In this paper, with regard to the permission-based access control system, we present a novel approach based on a machine-learning technique in order to support a user decision-making on the fly. We apply the K-NN (K-Nearest Neighbors) classification algorithm with necessary weighted modifications for malicious app classification, and use 152 Android permissions as features. Our experiment shows a superior classification result (93.5% accuracy) compared to other previous work. We expect that our method can help users make informed decisions at the installation step.

• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.25-36
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• 2017

As smartphone users have increased in recent years, various applications have been developed and used especially for Android-based mobile devices. However, malicious applications developed by attackers for malicious purposes are also distributed through 3rd party open markets, and damage such as leakage of personal information or financial information of users in mobile terminals is continuously increasing. Therefore, to prevent this, a method is needed to distinguish malicious apps from normal apps for Android-based mobile terminal users. In this paper, we analyze the existing researches that detect malicious apps by extracting the system call events that occur when the app is executed. Based on this, we propose a technique to identify malicious apps by analyzing the sequence similarity of kernel layer events occurring in the process of running an app on commercial Android mobile devices.