• 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.

• Knowledge Management Research
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• v.20 no.4
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• pp.149-168
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• 2019

In the era of the Fourth Industrial Revolution, digital transformation is emerging in the education and learning fields. As the use of the mobile Internet and mobile devices has become a daily life, mobile learning that supports a variety of learning in a mobile environment is drawing attention. Mobile learning applications (apps) are expected to expand their use by providing a convenient learning environment anytime, anywhere. This study investigates the use of mobile learning apps in English education, which is one of the most popular learning areas, and empirically examines the factors that influence the continuous use of mobile learning apps. In particular, it analyzes the differences between Chinese and Korean users. The results of this study provide theoretical and practical implications to promote the development of mobile apps suitable for mobile learning environments and the sustainable user growth in mobile learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2964-2983
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• 2015

As the Android operating system has become a key target for malware authors, Android protection has become a thriving research area. Beside the proved importance of system permissions for malware analysis, there is a lot of overlapping in permissions between malware apps and goodware apps. The exploitation of them effectively in malware detection is still an open issue. In this paper, to investigate the feasibility of neuro-fuzzy techniques to Android protection based on system permissions, we introduce a self-adaptive neuro-fuzzy inference system to classify the Android apps into malware and goodware. According to the framework introduced, the most significant permissions that characterize optimally malware apps are identified using Information Gain Ratio method and encapsulated into patterns of features. The patterns of features data is used to train and test the system using stratified cross-validation methodologies. The experiments conducted conclude that the proposed classifier can be effective in Android protection. The results also underline that the neuro-fuzzy techniques are feasible to employ in the field.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.118-125
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• 2021

This study's purpose is to examine the effects of mobile apps on learners' vocabulary acquisition and to analyze students' perceptions and opinions about the vocabulary app. To this end, this study set up a control group, which was given explicit instructions in the classroom by the instructor and an experimental group, which used a vocabulary app. The vocabulary acquisition test results suggested that the difference between the the two groups was insignificant. However, user satisfaction with regard to the mobile app was high, and the reasons given were the following: convenience, efficiency of memorizing, having fun while learning, and the app's interface. Based on these results, this study suggests that teachers should use mobile apps much more actively in classroom instruction, and encourge students to let apps play a more active role in their language studies.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.1
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• pp.45-55
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• 2018

Recently, because the arrival of the fourth industrial revolution era, many information and telecommunication services have grown rapidly in the mobile business market. So, companies are based Mobile Apps on user customized services and expanding their services. From the standpoint of the business, to generate revenue, the company needs to maintain the existing current computer environment and develop Mobile Apps to offer convenience in various areas such as finance, admiration, e-commerce and sales support. However, as the number of users increase due to expansion of various Mobile services, security threats that are related to Mobile Apps are increasing and its damage is also increasing. Due to the rapid technological transformation of Mobile devices using the Internet, the level of security threats to Smartphones are rising and getting more advance, so this thesis is structured as follows. In Chapter 2, it will look at the overall trends of Mobile Apps as related research. In Chapter 3, it will discuss various security concerns that related to the latest Mobile Apps and learn about the threatening factors. In Chapter 4, it will compare and analyze the threatening factors. Then it will find and suggest the possible plan. In Chapter 5, it will end with conclusion. Finally, to protect mobile devices from security threats, the environment of operating system which manages the resources and data of Apps needs to be protected. Also, it is important that users to have awareness and check activation FinTech technology security in the process of simple payment with fingerprint or IC card.

• Clinical and Experimental Pediatrics
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• v.63 no.6
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• pp.232-236
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• 2020

Background: Children today get access to smartphones at an early age. However, their ability to use mobile apps has not yet been studied in detail. Purpose: This study aimed to assess the ability of children aged 2-8 years to perform touchscreen gestures and follow prompting techniques, i.e., ways apps provide instructions on how to use them. Methods: We developed one mobile app to test the ability of children to perform various touchscreen gestures and another mobile app to test their ability to follow various prompting techniques. We used these apps in this study of 90 children in a kindergarten and a primary school in New Delhi in July 2019. We noted the touchscreen gestures that the children could perform and the most sophisticated prompting technique that they could follow. Results: Two- and 3-year-old children could not follow any prompting technique and only a minority (27%) could tap the touchscreen at an intended place. Four- to 6-year-old children could perform simple gestures like a tap and slide (57%) and follow instructions provided through animation (63%). Seven- and 8-year-old children could perform more sophisticated gestures like dragging and dropping (30%) and follow instructions provided in audio and video formats (34%). We observed a significant difference between the number of touchscreen gestures that the children could perform and the number of prompting techniques that they could follow (F=544.0407, P<0.05). No significant difference was observed in the performance of female versus male children (P>0.05). Conclusion: Children gradually learn to use mobile apps beginning at 2 years of age. They become comfortable performing single-finger gestures and following nontextual prompting techniques by 8 years of age. We recommend that these results be considered in the development of mobile apps for children.

• The KIPS Transactions:PartA
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• v.19A no.4
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• pp.187-194
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• 2012

This paper proposes a string analysis based system for classifying Android Apps that may access so called harmful sites, and shows an experiment result for real Android apps on the market. The system first transforms Android App binary codes into Java byte codes, it performs string analysis to compute a set of strings at all program points, and it classifies the Android App as bad ones if the computed set contains URLs that are classified because the sites provide inappropriate contents. In the proposed approach, the system performs such a classification in the stage of distribution before installing and executing the Apps. Furthermore, the system is suitable for the automatic management of Android Apps in the market. The proposed system can be combined with the existing methods using DNS servers or monitoring modules to identify harmful Android apps better in different stages.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.484-491
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• 2021

This study was undertaken to identify success factors of traditional market delivery apps and lead digital transformation of traditional markets. The success factors of traditional market delivery apps are represented by four variables: system characteristics of the app, delivery, products, and responsibility towards customer responses. These factors were analyzed to examine their impact on the operations performance. Data was collected by surveying 148 traditional market business owners. Results of the empirical analysis revealed that the app system characteristics, delivery characteristics, and product sales promotion, impart a significant effect on the operations performance. Conversely, the customer response characteristics showed no significant effects. This could be because some apps lack the function to check customer reviews and respond appropriately. Currently, where traditional market delivery apps are in the early stages of implementation and are gradually expanding, data obtained from this study helps to identify characteristics of traditional market delivery apps, and offers suggestions to create development indicators of the traditional market delivery apps by analyzing their effects on operational performance, thereby contributing to the revival of traditional markets through digital transformation.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.250-260
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• 2022

Mobile Banking Applications (MBAPs) is one of the recent fads in mobile trading applications (Apps). MBAPs permit users to execute exchanges of money and many more whenever it might suit them; however, the primary issue for mobile banking Apps is usability. Hardly any investigation analyzes usability issues dependent on user's age, gender, exchanging accomplices, or experience. The purpose of this study is to determine the degree of usability issues, and experience of mobile banking users. The survey employs a quantitative method and performs user experiment on 240 participants with six different tasks on the application's interface. The post experiment survey is done with concerning participants. On the other hand, banking experts and Information Technology (IT) expert's group is also involved after the experiment. Expert's opinions about existing mobile banking Apps and suggestions for improving usability of MBAPs are collected through physical means (like questionnaire and interview) and online means like Google form. After that comparison of the opinions of users and experts about MBAPs is performed. The experimentation measures the tasks usability of various mobile banking apps with respect to its effectiveness, efficiency, trustfulness, learnability, memorability and satisfaction. The usability testing was led at different Universities and the outcomes acquired show that there are privacy and trust issues with their mobile banking apps. There is also a gap between users and experts which should be minimized by applying customized usability models, modes concept like other application software and also by adding complete features of banking in MBAPs. It will benefit mobile banking apps users, developers and usability engineers by providing user-friendly which are up to the mark of user's requirements.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.374-376
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• 2022

The Malware App Analysis Tool is a system that analyzes Android-based apps by the AI-based algorithm defined in the tool and detects whether malware code is included. Currently, as the spred of smartphones is activated, crimes using malware apps have increased, and accordingly, security for malware apps is required. Android operating systems used in smartphones have a share of more than 70% and are open-source-based, so not only will there be many vulnerabilities and malware, but also more damage to malware apps, increasing demand for tools to detect and analyze malware apps. However, this paper is proposed because there are many difficulties in designing and developing a malware app analysis tool because the security functional requirements for the malware app analysis tool are not clearly specified. Through the developed protection profile, technology can be improved based on the design and development of malware app analysis tools, safety can be secured by minimizing damage to malware apps, and furthermore, trust in malware app analysis tools can be guaranted through common criteria.