• Journal of Korea Society of Industrial Information Systems
• /
• v.27 no.6
• /
• pp.115-126
• /
• 2022

The purpose of this study is to try to IPA(Importance-Performance Analysis) by applying text mining approaches to user review data for korea mobile banking applications, and to derive priorities for improvement. User review data on mobile banking applications of korea commercial banks (Kookmin Bank, Shinhan Bank, Woori Bank, Hana Bank), local banks (Gyeongnam Bank, Busan Bank), and Internet banks (Kakao Bank, K-Bank, Toss) that gained from Google playstore were used. And LDA topic modeling, frequency analysis, and sentiment analysis were used to derive key attributes and measure the importance and satisfaction of each attribute. Result, although 'Authorizing service', 'Improvement of Function', 'Login', 'Speed/Connectivity', 'System/Update' and 'Banking Service' are relatively important attributes when users use mobile banking applications, their satisfaction is not at the average level, indicating that improvement is urgent.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.1
• /
• pp.195-203
• /
• 2019

Mobile applications stores such as Google Play Store and Apple App Store, are widely used to distribute a variety of applications including finance, shopping, and entertainment. Recently, however, vulnerabilities of the mobile applications are likely to violate users' privacy such as personal information leakage. In this paper, we classify mobile applications that can be download from mobile stores, and analyze the personal information that could be leaked when users are using the mobile applications. As a result of analysis, we found that personal information are leaked in some widely used mobile applications in practice. On the basis of our experiment results, we propose some mitigations to enhance security of the mobile applications and prevent leakage of personal information.

• The Journal of Society for e-Business Studies
• /
• v.24 no.2
• /
• pp.1-14
• /
• 2019

Because of the characteristics of game software, it is important to quickly identify and reflect users' needs into game software after its launch. However, most sites such as the Google Play Store, where users can download games and post reviews, provide only very limited and ambiguous classification categories for game reviews. Therefore, in this paper, we develop an automatic classification system for game reviews that categorizes reviews into categories that are clearer and more useful for game providers. The developed system converts words in reviews into vectors using word2vec, which is a representative word embedding model, and classifies reviews into the most relevant categories by measuring the similarity between those vectors and each category. Especially, in order to choose the best similarity measure that directly affects the classification performance of the system, we have compared the performance of three representative similarity measures, the Euclidean similarity, cosine similarity, and the extended Jaccard similarity, in a real environment. Furthermore, to allow a review to be classified into multiple categories, we use a threshold-based multi-category classification method. Through experiments on real reviews collected from Google Play Store, we have confirmed that the system achieved up to 95% accuracy.

• Journal of Korea Game Society
• /
• v.15 no.6
• /
• pp.183-190
• /
• 2015

Construct2 Game Engine is development by in United Kingdom production company Scirra. Construct 2 game engine to be used globally, the most excellent technical strength and visibility in the 2D game engine has grown to high engine. The game engine created by the 'Kongbin&Domino'. 'Kongbin&Domino' game, it began commercialization in the Google store and Apple's App Store. It advances the quality evaluation of the case of the production process and the game engine. Researched that can contribute to a better production. In the future, throughout the Research, it is to be contributed to the development of the game industry is conducting research to support the game development process which can be facilitated by the game content creation.

• KIISE Transactions on Computing Practices
• /
• v.22 no.8
• /
• pp.351-356
• /
• 2016

In recent years, as smartphones with Android platforms expand, the number of Android applications increases. Android applications implement Java and XML to compose the user interface, among other things. Between Java and XML, various problems may occur. Nonetheless, static analysis research and tools are not sufficient. In this paper we will list the problems which may occur between Java and XML. Subsequently, we will propose a detection method for them. Using the proposed technique, we found 172 Android-specific problems and 35 performance drop issues in 150 Android applications in the Google Play Store. We would like to contribute to research into static analysis and software quality improvement.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2014.11a
• /
• pp.495-498
• /
• 2014

최근 스마트폰을 이용한 인터넷 사용이 증가하면서 카페나 영화관과 같은 공공장소에 많은 Access Point(AP)들이 설치되어 있다. 하지만 이러한 AP 대부분이 외부 공격에 무방비하게 노출되어 위험성이 대두되고 있다. 대표적인 공격으로 사용자와 AP간 통신에 끼어들어 데이터를 도청하거나 위 변조하는 Man-In-The-Middle(MITM) 공격이 있다. MITM 공격에 대한 대응책으로 통신간 암호화가 있지만, 모든 통신에 암호화를 적용하는 것은 많은 비용이 발생하기 때문에 현실적으로 불가능하다. 실제로 구글 플레이스토어에 등록된 100개의 무료 인기 어플리케이션 중 모든 메시지에 암호화 통신을 사용하는 어플리케이션은 없으며, 부분적으로 사용하는 어플리케이션은 43개임을 확인하였다. 본 논문에서는 앞서 설명한것과 같이 통신간 암호화를 하지 않는 어플리케이션을 MITM 공격으로부터 보호하기 위한 메시지 인증 기반 무결성 검증 방법을 제안하여 안전한 어플리케이션-서버 통신 모델 개발에 기틀을 마련한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2018.10a
• /
• pp.729-732
• /
• 2018

모바일 게임 산업의 발달로 많은 사용자들이 게임을 이용하면서, 그들의 만족감을 사용리뷰를 통해 드러낸다. 실제로 각 리뷰의 범주가 모두 다르지만 현재 구글 플레이 앱스토어(Google Play App Store)의 게임 리뷰 범주는 3가지로 매우 제한적이다. 따라서 본 연구에서는 빠르고 정확한 고객의 요구를 필요로 하는 게임 소프트웨어의 특성을 고려하여 게임 리뷰를 입력했을 때, 게임의 운영 및 시스템에 맞도록 리뷰의 카테고리를 세분화하고 만족도를 분석하는 시스템을 개발한다. 제안 시스템은 인공신경망 모델인 CNN을 평점을 기반으로 훈련시켜 리뷰에 대한 만족도를 도출한다. 또한 Word2Vec을 이용해 단어들 간의 유사도를 구하고, 이를 활용한 단어 배열을 이용하여 가장 스코어가 높은 카테고리로 배정한다. 본 논문은 제안한 리뷰 만족도 및 카테고리 분류 시스템이 실제 효과적으로 리뷰를 보다 의미 있는 정보로써 제공할 수 있음을 보인다.

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

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.6
• /
• pp.907-913
• /
• 2022

Approximately 70% of smartphone users around the world use Android operating system-based smartphones, and malicious apps targeting these Android platforms are constantly increasing. Google has provided "Google Play Protect" to respond to the increasing number of Android targeted malware, preventing malicious apps from being installed on smartphones, but many malicious apps are still normal. It threatens the smartphones of ordinary users registered in the Google Play store by disguising themselves as apps. However, most people rely on antivirus programs to detect malicious apps because the average user needs a great deal of expertise to check for malicious apps. Therefore, in this paper, we propose a method to classify unnecessary malicious permissions of apps by using only the categories and permissions that can be easily confirmed by the app, and to easily detect malicious apps through the classified permissions. The proposed method is compared and analyzed from the viewpoint of undiscovered rate and false positives with the "commercial malicious application detection program", and the performance level is presented.

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