• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.17-24
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• 2023

Mobile apps frequently request permission to access sensitive data for user convenience. However, while using mobile applications, sensitive and personal data has been leaked even if users do not allow it. To deal with this problem, Google App Store has required developers to disclose how the mobile app handles user data in a privacy policy. However, users are not certain that the privacy policy describes all the app's behavior. They have no choice but to rely on the privacy policy to confirm how the app uses data. This study designed a system that checks the reliability of privacy policies by analyzing the privacy policy texts and mobile apps. First, the system extracts and analyzes the privacy policy texts to check which personal data the privacy policy discloses that the mobile apps can collect. After analyzing which data apps can access using android static analysis, we compare both results to analyze the reliability of privacy policies. For the experiment, we collected the APK files and metadata of about 13K android apps registered in the Google Play Store and preprocessed the apps by four conditions. According to the comparison between privacy policies and mobile app behavior, many apps can access more personal data than disclosed in the privacy policy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.951-959
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• 2017

In this paper, we design and implement an Android-based Hangul food menu recognition application that recognizes characters from images captured by a smart phone. Optical Character Recognition (OCR) technology is divided into preprocessing, recognition and post-processing. In the preprocessing process, the characters are extracted using Maximally Stable Extremal Regions (MSER). In recognition process, Tesseract-OCR, a free OCR engine, is used to recognize characters. In the post-processing process, the wrong result is corrected by using the dictionary DB for the food menu. In order to evaluate the performance of the proposed method, experiments were conducted to compare the recognition performance using the actual menu plate as the DB. The recognition rate measurement experiment with OCR Instantly Free, Text Scanner and Text Fairy, which is a character recognizing application in Google Play Store, was conducted. The experimental results show that the proposed method shows an average recognition rate of 14.1% higher than other techniques.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.3
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• pp.159-168
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• 2017

Smartphone malware has increased because Smartphone users has increased and smartphones are widely used in everyday life. Since 2012, Android has been the most mobile operating system. Owing to the open nature of Android, countless malware are in Android markets that seriously threaten Android security. Most of Android malware detection program does not detect malware to which bypass techniques apply and also does not detect unknown malware. In this paper, we propose lightweight method for detection of Android malware using static analysis and deep learning techniques. For experiments we crawl 7,000 apps from the Google Play Store and collect 6,120 malwares. The result show that proposed method can achieve 98.05% detection accuracy. Also, proposed method can detect about unknown malware families with good performance. On smartphones, the method requires 10 seconds for an analysis on average.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.6
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• pp.1477-1489
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• 2019

In this study, we analyzed the privacy policies of 50 Android applications that are on the top chart in EU members to present the methods for enhancing transparency based on GDPR (General Data Protection Regulation). Based on the guidelines in relation to transparency stipulated in WP29, this study extracted factors of transparency in order to ensure transparency of privacy data processing and carried out the verification procedures for each factor. The results revealed that the privacy policies provided in Google Play Store and applications need to be matched, the descriptions of the privacy policies need to be written in clear and plain language for readers to understand easily. and that it is necessary to provide information quickly and improve the descriptions of information which the data controller discloses. The research findings of this study could be used as a preliminary data for proactive responses to the EU's GDPR by substantially complying with the transparency of GDPR.

• Smart Media Journal
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• v.12 no.6
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• pp.15-26
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• 2023

As face-to-face communication has become difficult due to the COVID-19 pandemic, studies have been conducted to understand the impact of non-face-to-face communication, but there is a lack of research that examines this through messenger application reviews. This study aims to identify the impact of the pandemic through Latent Dirichlet Allocation (LDA) topic modeling by collecting review data of 메신저 applications in the Google Play Store and suggest service strategies accordingly. The study categorized the data based on when the pandemic started and the ratings given by users. The analysis showed that messenger is mainly used by middle-aged and older people, and that family communication increased after the pandemic. Users expressed frustration with the application's updates and found it difficult to adapt to the changes. This calls for a development approach that adjusts the frequency of updates and actively listens to user feedback. Also, providing an intuitive and simple user interface (UI) is expected to improve user satisfaction.

• Journal of Industrial Convergence
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• v.22 no.4
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• pp.11-19
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• 2024

The purpose of this study was to analyze user reviews of running applications using text mining. This study used user reviews of Nike Run Club and Runkeeper in the Google Play Store using the selenium package of python3 as the analysis data, and separated the morphemes by leaving only Korean nouns through the OKT analyzer. After morpheme separation, we created a rankNL dictionary to remove stopwords. To analyze the data, we used TF, TF-IDF and LDA topic modeling in text mining. The results of this study are as follows. First, the keywords 'record', 'app', and 'workout' were identified as the top keywords in the user reviews of Nike Run Club and Runkeeper applications, and there were differences in the rankings of TF and TF-IDF. Second, the LDA topic modeling of Nike Run Club identified the topics of 'basic items', 'additional features', 'errors', and 'location-based data', and the topics of Runkeeper identified the topics of 'errors', 'voice function', 'running data', 'benefits', and 'motivation'. Based on the results, it is recommended that errors and improvements should be made to contribute to the competitiveness of the application.

• Journal of Society of Preventive Korean Medicine
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• v.19 no.2
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• pp.103-112
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• 2015

Objective : To evaluate the status of mobile personal health records (mPHR) applications of Atopic Dermatitis, assessing general characteristics, information content, features of PHR content and functions. Method : Searches were conducted from Android's Google Play and iOS's App Store. Main criteria used to include mPHRs were: providing health information of PHR function of Atopic Dermatitis; operating in Korean or English; for human. Selected mPHRs were analyzed considering general characteristics, information contents, data elements, and application features. Results : 19 applications were included in this study. 15 were providing health information. Data elements of information included general information, symptom, diagnosis, treatment, prevention, management and FAQ. No single application contained all seven data elements. Only Eight applications had PHR function. In the features analysis, one PHR applications contained all eight PHR functional features; saving profile function, profiles supported, password, import data, export data, information provided, progress chart and push-up alarm. Conclusion : mPHR is an emerging health care technology. The majority of existing mPHR applications only provide one-way information. Application designed to help users and doctors to exchange mutual information was the only one. Also, there was no application that can record the Traditional Korean Medicinal treatment information. However, as the mobile market continues to expand it is likely that more comprehensive mPHRs will be developed in the near future. New advancements in mobile technology can be utilized to enhance Tranditional Korean Medical health care.

• The Journal of the Korea Contents Association
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• v.15 no.3
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• pp.352-361
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• 2015

Tea is one of the three most consumed drinks in the world along with coffee and cocoa, and it represents culture and tradition. There are more than 1,000 tea-related smartphone applications registered in the Apple App Store and Google Play. This study examined, for the consumers of the 20's, if there are differences in consumer preferences for tea-related applications based on gender, age, tea consumption amount and tea drinking duration. Based on surveys of 169 tea consumers, this study found that there were significant differences in consumer preferences for tea-related applications based on age and tea drinking amount. The applications of 'tea places,' 'entertainment,' and 'tea timer' were preferred by the consumers of 20's and 'etiquette,' 'tea ceremony,' 'teaware,'and 'tea information recording' were favored by the consumers of 30's and older. The consumers with higher drinking amount showed higher preferences for tea etiquette related applications. There were no significant differences for tea-related applications based on gender and tea drinking duration. The result of the study is expected to contribute to the development of tea related applications with higher appeals to consumers as well as traditional Korean drinks.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.163-171
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• 2020

Currently, most of the mobile game market releases games through Google play and App Store, which have a high share. Because it uses a third-party platform, only the payment API system provided must be used, and third-party platform pays the game company after excluding certain fees. Because game companies do not know whether or not to refund items and cannot get back items through third party transactions, users and professional websites are continuously appearing that exploit refunds. In this thesis, after analyzing problems of existing payment method and presenting a payment model using blockchain smart contract, we analyzed differences from existing model in terms of transparency, decentralization(fee), efficiency, and as a result, payment model using smart contract has low commission through P2P transaction without third parties and transparent transaction record, preventing item forgery and refund. Later, the proposed payment model would lead to the culling of companies acting on behalf of refunds for words that deviate from moral ethics such as "Refund OK even with items" and resolve the problem of unreasonable fees that arise through third-party platforms.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.365-385
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• 2022

The easy payment service is a payment and remittance service that uses a simple authentication method. As online transactions have increased due to COVID-19, the use of an easy payment service is increasing. At the same time, electronic financial industries such as Naver Pay, Kakao Pay, and Toss are diversifying the competition structure of the easy payment market; meanwhile overseas fintech companies PayPal and Alibaba have a unique market share in their own countries, while competition is intensifying in the domestic easy payment market, as there is no unique market share. In this study, the participants in the easy payment market were classified as electronic financial companies, mobile phone manufacturers, and financial companies, and a SWOT analysis was conducted on the representative services in each industry. The analysis examined the user reviews of Google Play Store via a topic modeling analysis, and it employed positive topics as strengths and negative topics as weaknesses. In addition, topic modeling was conducted by dividing news articles into political, economic, social, and technology (PEST) articles to derive the opportunities and threats to easy payment services. Through this research, we intend to confirm the service capabilities of easy payment companies and propose a service activation strategy that allows gaining the upper hand in the market.