• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.201-203
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• 2019

Apps and games continue to grow in size as new content comes and compete on Google Play. As apps and games grow in size, app installs through the Google Play store are decreasing. The article talks about the structure and limitations of the existing support model, APK, and discusses the new support model, the Android App Bundle (AAB) structure. We will also look into future prospects.

• Smart Media Journal
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• v.2 no.1
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• pp.17-26
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• 2013

Electronic bulletin boards, has been used as an effective tool in various information delivery. However, many electronic bulletin board as a one-way information passed by the interactivity is lacking. In this paper, the interaction of the information, while maintaining an electronic bulletin board that can be operated on a variety of platforms, the Android-based software and hardware for the design and implementation. The interaction of users of electronic bulletin boards, and information can be naturally-type content support Android framework was designed to allow Android APP. Android APP using the administrator also was designed automatic installation and FORUMS so that you can run. Naturally gather information, and all the people that interact through bulletin boards, so you can take advantage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.377-380
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• 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
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• v.10 no.12
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• pp.1-6
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• 2019

In this paper, we have developed an app that can control IPTV - Miracast and the Internet with Android 7.0 on the embedded board. The app can be controlled by the remote control of IPTV and can receive TV when using IPTV. And Miracast and Embedded board are put into the power saving mode. When one mode is selected in this way, the other two modes enter the power saving mode and the power saving control technology is applied to reduce energy consumption. The board used in this paper was Android version 7.1.2 version of Raspberry pie 3B / B + and Asus Tinker board s, and Android Studio program was used to make the app and a synchronization control program was also developed to operate with IPTV remote control. The operation of the Android start program using the power saving power control technology and the remote control synchronization control program developed in this way is confirmed to be normal operation as a result of applying to the actual IPTV.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3999-4005
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• 2013

We forecast that the scale of mobile market will be large scale according to the twenty million times of smart phone's user is arrived. The type of software development is being transferred into mobile-based App. or cloud computing-based service from web-based software. Currently both Google's android and Apple's IOS are known for two prominent platforms. Existing modeling techniques cannot be applied into the case of mobile application which is executed those platforms. Therefore, we suggest a modeling technique that is customized existing modeling techniques into android-based software development. That is, we propose an analysis and design techniques which are needed into android-based mobile smart environment.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.141-149
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• 2023

Repacked mobile apps constitute about 78% of all malware of Android, and it greatly affects the technical ecosystem of Android. Although many methods exist for repacked app detection, most of them suffer from performance issues. In this manuscript, a novel method using the Constant Key Point Selection and Limited Binary Pattern (CKPS: LBP) Feature extraction-based Hashing is proposed for the identification of repacked android applications through the visual similarity, which is a notable feature of repacked applications. The results from the experiment prove that the proposed method can effectively detect the apps that are similar visually even that are even under the double fold content manipulations. From the experimental analysis, it proved that the proposed CKPS: LBP method has a better efficiency of detecting 1354 similar applications from a repository of 95124 applications and also the computational time was 0.91 seconds within which a user could get the decision of whether the app repacked. The overall efficiency of the proposed algorithm is 41% greater than the average of other methods, and the time complexity is found to have been reduced by 31%. The collision probability of the Hashes was 41% better than the average value of the other state of the art methods.

• Journal of KIISE
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• v.41 no.9
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• pp.707-714
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• 2014

In general, the benign apps transmit privacy information to the external to provide service to users as the malicious app does. In other words, the behavior of benign apps is similar to the one of malicious apps. Thus, the benign app can be easily manipulated for malicious purposes. Therefore, the malicious apps as well as the benign apps should notify the users of the possibility of privacy information leakage before installation to prevent the potential malicious behavior. In this paper, We propose the method to detect leakage of privacy information on the android app by analyzing API inter-dependency and shortest distance. Also, we present LeakDroid which detects leakage of privacy information on Android with the above method. Unlike dynamic approaches, LeakDroid analyzes Android apps on market site. To verify the privacy information leakage detection of LeakDroid, we experimented the well-known 250 malicious apps and the 1700 benign apps collected from Android Third party market. Our evaluation result shows that LeakDroid reached detection rate of 96.4% in the malicious apps and detected 68 true privacy information leakages inside the 1700 benign apps.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.65-72
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• 2020

In this paper, we developed a web-based DApp system based on a private blockchain by applying machine learning techniques to automatically identify Android malicious apps that are continuously increasing rapidly. The optimal machine learning model that provides 96.2587% accuracy for Android malicious app identification was selected to the authorized experimental data, and automatic identification results for Android malicious apps were recorded/managed in the Hyperledger Fabric blockchain system. In addition, a web-based DApp system was developed so that users who have been granted the proper authority can use the blockchain system. Therefore, it is possible to further improve the security in the Android mobile app usage environment through the development of the machine learning-based Android malicious app identification block chain DApp system presented. In the future, it is expected to be able to develop enhanced security services that combine machine learning and blockchain for general-purpose data.

• The Journal of the Convergence on Culture Technology
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• v.2 no.3
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• pp.35-40
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• 2016

This study is about developing an Android application that provides information on customized styling and the app was made to offer assistance in coordinating users' clothing. It keeps the record on clothing items users wore and uses it as coordination information, and prepares styling by referring to user-specific clothing management data. The photos can taken during shopping or can be taken from smart phone gallery, and the images searched through Daum OpenAPI can be saves in the app. Using the saved photos of items and clothes that were previously worn, the app provides styling recommendations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.429-432
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• 2012

Mobile devices diffusion begins by the iPhone and spreads by the Android. A widely used mobile devices is Smartphone(iPhone, Android, Bada, WindowPhone7, BlackBerry, etc) and Tablet(iPad, Android). In the past, we have developed a dedicated application for device. But, Now we must develop a application by considering the characteristics of the operating system. Accordingly, many problems occurred and other developmet methods have emerged. In this paper, we learn about MobileHybridApp development tool-oriented One Source Multi Use-and compare the differences, propose a method to develop context-sensitive.