• 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 Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.399-410
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• 2018

In Android smartphones, many apps are developed as service apps to run in the background. If the memory is insufficient, Android forcibly terminates not only user apps that have not used the CPU for a long time, but also service apps. However, a service app is automatically re-launched after a short period of time, so that it continuously consumes memory space. This paper analyzes the number of running service apps and their memory usage in users' smartphones. The number of service apps accounts for up to 65% of the total number of running apps, and their memory usage accounts for up to 55% of the total memory. Moreover, we investigate the effect of the number of running service apps on the response time of smartphones and apps. As the number of service apps increases, the launching time of user apps increases to 22 times. The booting time and app installation time significantly increase with the number of service apps.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.949-958
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• 2022

Modern people have many kinds of clothes for individuals, and not just for storing clothes, but also for managing the condition of the closet, and users of smart closets created smart closets that provide daily convenience and optimal closet conditions, suggesting the possibility of developing smart furniture for various environments. In this developed system, smart closet is controlled using app inventor and touch LCD through bluetooth wireless communication, based on Arduino MEGA and user's clothes is recommended depending on the weather. In addition, this smart closet is designed with real-time weather status checking and easy ventilation function. It was implemented through the Arduino and app inventor program so that the weather can be printed on the LCD screen and the user's suitable clothes can be recommended to the application.

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.101-106
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• 2018

The purpose of this study is to analyze the patterns of unconsciousness smartphone use by using an app and a self-administered survey on smartphone addiction comparatively and examine differences between recognition and behavior about actual smartphone use and examine how smartphone addiction influences learning. With an app installed in smartphones, this author collected and analyzed data about users' unconsciousness using patterns for a month. According to the results, there were significant differences found in users' recognition and actual time for use and also frequency of turning on the display. Also, 22% of the subjects used their smartphone over 8 hours a day, and 76% more than 5 hours. Over 95% turned on the display more than 100 times a day, and in extreme cases, they did more than 300 times. In the meantime, users not only in the smartphone addiction high risk group and the potential risk group but also in the general user group are found to use their smartphone too long and too much and frequently turn on the display. The apps that the general user group is mainly using are entertaining apps, and their school records are rather good, so excessive use does not always lead to addiction or learning disorder. Therefore, if we develop more diverse contents for learning and provide digital literacy education, smartphone use will bring more positive effects instead. In follow-up research, the app should be corrected to collect more accurate information, and as variables in personal areas, this researcher will also measure depression, anxiety, stress, self-esteem, and emotional control, and so on to see how they are associated with smartphone use.

• Convergence Security Journal
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• v.14 no.4
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• pp.61-71
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• 2014

In recent years, malwares in Android smartphones are becoming increased explosively. Since a great deal of appsare deployed day after day, detecting the malwares requires commercial anti-virus companies to spend much time and resources. Such a situation causes malwares to be detected after they have become already spread. We propose a scheme called TAU that dynamically tracks application behaviors to specify apps with potential security risks. TAU keeps track of how a user's interactions to smartphones incurs the app installation, the route of app spread, and the behavior of app execution. This tracking specifies apps that have the possibility of attacking the smartphones using the drive-by download and update attack schemes. Moreover, the tracked behaviors are used to decide whether apps are repackaged or not. Therefore, TAU allows anti-virus companies to detect malwares efficiently and rapidly by guiding to preferentially analyze apps with potential security risks.

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.91-96
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• 2017

In this paper, we aim to respond efficiently to crime by using Arduino and smartphone apps in response to increasing number of house-breaking crimes. It receives the signal of the sensor installed in the house and connects it with the app of the smartphone. To use the app, you can download the app from the user's smartphone, launch the app, and operate the operation outside the home, not only inside the house, by linking the executed app. Among the sensors installed in the house, the movement detection sensor is used to enhance the security, and the gas leakage sensor and the flame detection sensor can be used to easily detect the risk of fire and to prevent the fire early. Security is further enhanced by the ability to remotely control the front door with a smartphone. After that, various sensors can be added and it can be developed as a WiFi module in addition to the Bluetooth module.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.85-98
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• 2021

Domestic delivery app services are taking a leap forward as the non-face-to-face culture spreads due to the COVID 19 situation and the industrial scale is also growing. In the expanding delivery app service market, we try to verify the structural relationship between variables by empirically analyzing the influencing factors of users' trust in rational and emotional factors. Delivery app service users trust and discriminate parameters in the relationship between rational and emotional factors. Satisfaction according to the trust of a valid delivery app service and service expansion model through word of mouth was designed. It was verified through a hypothesis whether it had an effect, and it can be used as a variety of service strategies for delivery app service users.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.11
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• pp.337-346
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• 2023

There is a need to develop an app for a caregiver health management that can provide continuous management in response to changes over time, because elderly people have low digital utilization capabilities, difficulty maintaining regular and continuous self-management. Based on this need, this study designed an app with a user-friendly UI and simple structure for the elderly. The app developed in this study supports regular management of health data such as blood pressure, blood sugar, and heart rate, as well as specific information on physical, disease, cognitive, communication, and environment in the care field. The app developed in this study supports care services by automatically entering data through integration with health management devices, automatically analyzing and visually representing recorded data to understand trends and volatility, and adding scalability to connect with various health management and medical support platforms. The effectiveness and satisfaction of the developed app were confirmed to be significant in the field verification results.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.115-121
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• 2017

The Korea metropolitan areas have the largest of population density in OECD countries. Those people who use public transportation is facing many difficulties in commuting and going to school. There are many applications to help this situation. However, those applications inform a regular timetable and also offer a real-time alarm to user by user's passive action. In this paper, we design and implement the application that give the real-time traffic information and the arrival notification message about subway, bus and foot to user.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2272-2279
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• 2014

Mobile applications are software systems running on handheld devices, such as smartphones, PDAs, tablets and so on. The market of mobile application has rapidly expanded in the past few years. In this paper, we present a novel approach to track smartphone application usage from a event logs on the mobile device and analyzed both on client system and usage analysis server. We implemented our client system on Android device based usage analytics platform. Based on the analysis server system, we obtained over 47,000 user base, and we get the user's app usage informations on realtime. In this paper, we describe a large scale deployment-based research for a smartphone usage patterns and usage information visualization techniques.