• Journal of The Korean Association of Information Education
• /
• v.16 no.2
• /
• pp.223-231
• /
• 2012

Recently, We need a change of our education, Owing to trend of smart phone, approaching Digital Natives. We need some Teaching-Learning method, materials, softwares which realize Student-centered, Customized education more than E-learning, U-learning. Thus, In demand of This, This study will suggest a creative idea that how to design and produce smart-phone application which refers to 800 English words in elementary school recommended The Ministry of Education, Science, and Technology in Android Platform.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.1
• /
• pp.193-198
• /
• 2018

These days, computer system has been introduced for work in most areas, including manufacturing, medical service, education, logistics, and other services. To increase work efficiency, mobile system has been more applied. However, on the basis of Android applications, it is hard for laypersons who have no enough knowledge of Android, or computer team members in general firms to develop mobile App. As a result, work efficiency comes to low. Therefore, this study designed and developed the mobile application for anthropometry data input of medical checkup with the use of App Inventor. As shown in the designed and developed mobile application, it is expected to develop a work process mobile App, it is expected to develop a work process mobile App easily and quickly with the use of App Inventor and to increase work efficiency even though there is not much knowledge of mobile application development.

• Journal of the Ergonomics Society of Korea
• /
• v.36 no.5
• /
• pp.437-446
• /
• 2017

Objective: This study aims to draw an efficient UI design by comparing the usability of App drawer and single-layered home screens, which are smartphone home screens. Background: Because smartphone home screen is frequently used including the installation, deletion, and editing of APPs, it should be designed with easily controllable information structure. There is a need to seek a user-friendly UI by comparing the usability of App drawer and single-layered home screens, of which methods to search Apps are different. There is also a need to examine an efficient UI and the factors to improve from the user perspective. Method: This study targeted 30 Android OS and iOS users to evaluate the App drawer and single-layered home screens, of which UI structures are different. Each participant was instructed to carry out an App searching task and App deleting task, and the execution time and the number of errors were measured. After the tasks were completed, they evaluated satisfaction through a questionnaire survey. Results: In the App searching task with low task level, there was no difference in execution level between the App drawer and single-layered home screens. However, the single-layered home screen showed higher efficiency and accuracy in the App deleting task with high task level. As for the group difference according to use experience, there was no difference in satisfaction among Android OS users, but iOS user satisfaction with single-layered home screen with which they were familiar was higher. Conclusion: As for home screen usability, the single-layered home screen UI structure can be advantageous, as task level is higher. Repulsion was higher, when users, who had used easier UI, used complex UI in comparison with user satisfaction, when users familiar with complex UI used easier UI. A UI indicating the current status with clear label marking through a task flow chart-based analysis, and a UI in which a user can immediately recognize by exposing hidden functions to the first depth were revealed as things to improve. Application: The results of this study are expected to be used as reference data in designing smartphone home screens. Especially, when iOS users use Android OS, the results are presumed to contribute to the reduction of predicted barriers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.377-380
• /
• 2022

An application called an app can be downloaded and used on mobile devices. Among them, Android-based apps have the disadvantage of being implemented on an open source basis and can be exploited by anyone, but unlike iOS, which discloses only a small part of the source code, Android is implemented as an open source, so it can analyze the code. However, since anyone can participate in changing the source code of open source-based Android apps, the number of malicious codes increases and types are bound to vary. Malicious codes that increase exponentially in a short period of time are difficult for humans to detect one by one, so it is efficient to use a technique to detect malicious codes using AI. Most of the existing malicious app detection methods are to extract Features and detect malicious apps. Therefore, three ways to select the optimal feature to be used for learning after feature extraction are proposed. Finally, in the step of modeling with optimal features, ensemble techniques are used in addition to a single model. Ensemble techniques have already shown results beyond the performance of a single model, as has been shown in several studies. Therefore, this paper presents a plan to select the optimal feature and implement a learning model for Android app-based malicious code detection.

• Journal of the Korea Convergence Society
• /
• v.8 no.3
• /
• pp.49-61
• /
• 2017

Recently, convenience and usability are increasing with the development and deployment of various mobile applications on the Android platform. However, important information stored in the smartphone is leaked to the outside without knowing the user since the malicious mobile application is continuously increasing. A variety of mobile vaccines have been developed for the Android platform to detect malicious apps. Recently discovered server-based polymorphic(SSP) malicious mobile apps include obfuscation techniques. Therefore, it is not easy to detect existing mobile vaccines because some other form of malicious app is newly created by using SSP mechanism. In this paper, we analyze the correlation between the similarity of the method in the DEX file constituting the core malicious code and the permission similarity measure through APK de-compiling process for the SSP malicious app. According to the analysis results of DEX method similarity and permission similarity, we could extract the characteristics of SSP malicious apps and found the difference that can be distinguished from the normal app.

• Journal of Internet Computing and Services
• /
• v.14 no.6
• /
• pp.125-139
• /
• 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 Internet of Things and Convergence
• /
• v.6 no.2
• /
• pp.1-10
• /
• 2020

The mobile application based on the Android platform is simple to decompile, making it possible to create malicious applications similar to normal ones, and can easily distribute the created malicious apps through the Android third party app store. In this case, the Android malicious application in the smartphone causes several problems such as leakage of personal information in the device, transmission of premium SMS, and leakage of location information and call records. Therefore, it is necessary to select a optimal model that provides the best performance among the machine learning techniques that have published recently, and provide a technique to automatically identify malicious Android apps. Therefore, in this paper, after adopting the feature engineering to Android apps on official test set, a total of four performance evaluation experiments were conducted to select the machine learning model that provides the optimal performance for Android malicious app detection.

• Journal of Digital Contents Society
• /
• v.14 no.3
• /
• pp.381-390
• /
• 2013

Almost all the mobile phone users already moved or are now moving away to smartphones for their various applications like games. If we are to speak about game applications, due to the performance limits of smartphones, 2D games are predominant over 3D games in every app. store. In this paper, we implement a 3D cube game application by porting an existing visual c++ irrlicht cube application to android platform library using the android Native Development Kit. After the porting is done, we add a few new features for more fun. Because the android NDK makes the existing C/C++ codes run directly on the android operating systems, we found by real execution tests that our 3D cube app. is well executed on a low-end android smartphone without any performance problem.

• Journal of Korea Multimedia Society
• /
• v.20 no.5
• /
• pp.827-834
• /
• 2017

Android's inter-application access enriches its application ecosystem. However, it exposes security vulnerabilities where end-user data can be exploited by attackers. While existing techniques have focused on minimizing the risks of inter-application access, they either suffer from inaccurate risk detection or are primarily available to expert users. This paper introduces a novel technique that automatically analyzes potential risks between a set of applications, aids end-users to effectively assess the identified risks by crowdsourcing assessments, and generates an access control policy which prevents unsafe inter-application access at runtime. Our evaluation demonstrated that our technique identifies potential risks between real-world applications with perfect accuracy, supports a scalable analysis on a large number of applications, and successfully aids end-users' risk assessments.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.9
• /
• pp.139-147
• /
• 2016

In recent, android application developments have been done widely that intensify smart phone utilization. In this paper, we propose a curriculum that undergraduate students can improve their mobile programming abilities as well as integrate experiences of application development based on android. And also a series of practices to advance their sense of accomplishment are added by offering an opportunity to carry out a real project to use a variety of sensors embedded in smart phone during the course of study. The project is composed of a series of modules for implementing a trekking App that helpful to people who enjoy spending time in outdoors through their favorite activities such as trekking, cycling, and climbing with their own smart phones. Through practical curriculum operation and project implementation, we show that the proposed curriculum is appropriate to a mobile programming education that combine learning and practice.