• Title/Summary/Keyword: 모바일 앱 분류

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Development of a Sales Support Application Based on E-Business Cards (전자명함 기반의 영업지원 앱 개발)

  • Byun, Dae-Ho
    • The Journal of the Korea Contents Association
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    • v.18 no.5
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    • pp.464-471
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    • 2018
  • The business card is regarded as the simplest means as well as a tool the most likely to use as a means of sales. Every day, we are exchanging business cards with many customers, but the paper based business card is easy to discard and difficult for searching information on the business card. As a solution, if we take a photographed business card with a smart phone and make it into a database, we can easily obtain customer information we wanted for sales at any time. In this study, we develop an application solution based on electronic business card database that supports sales management. The system operates in a cloud environment and has various decision support functions such as customer's human network management, customer classification, and finding prospective customers.

Modeling and Selecting Optimal Features for Machine Learning Based Detections of Android Malwares (머신러닝 기반 악성 안드로이드 모바일 앱의 최적특징점 선정 및 모델링 방안 제안)

  • Lee, Kye Woong;Oh, Seung Taek;Yoon, Young
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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    • pp.164-167
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    • 2019
  • 모바일 운영체제 중 안드로이드의 점유율이 높아지면서 모바일 악성코드 위협은 대부분 안드로이드에서 발생하고 있다. 그러나 정상앱이나 악성앱이 진화하면서 권한 등의 단일 특징점으로 악성여부를 연구하는 방법은 유효성 문제가 발생하여 본 논문에서는 다양한 특징점 추출 및 기계학습을 활용하여 극복하고자 한다. 본 논문에서는 APK 파일에서 구동에 필요한 다섯 종류의 특징점들을 안드로가드라는 정적분석 툴을 통해 학습데이터의 특성을 추출한다. 또한 추출된 중요 특징점을 기반으로 모델링을 하는 세 가지 방법을 제시한다. 첫 번째 방법은 보안 전문가에 의해 엄선된 132가지의 특징점 조합을 바탕으로 모델링하는 것이다. 두 번째는 학습 데이터 7,000개의 앱에서 발생 빈도수가 높은 상위 99%인 8,004가지의 특징점들 중 랜덤포레스트 분류기를 이용하여 특성중요도가 가장 높은 300가지를 선정 후 모델링 하는 방법이다. 마지막 방법은 300가지의 특징점을 학습한 다수의 모델을 통합하여 하나의 가중치 투표 모델을 구성하는 방법이다. 최종적으로 가중치 투표 모델인 앙상블 알고리즘 모델을 사용하여 97퍼센트로 정확도가 개선되었고 오탐률도 1.6%로 성능이 개선되었다.

Design and implementation of a satisfaction and category classifier for game reviews based on deep learning (딥러닝 기반 게임 리뷰 만족도 및 카테고리 분류 시스템 설계 및 개발)

  • Yang, Yu-Jeong;Lee, Bo-Hyun;Kim, Jin-Sil;Lee, Ki Yong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.729-732
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    • 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.

A Study on the Strategy of Platform Operator for Free Mobile Data : from the Perspectives of Business Opportunity and Risk (모바일 데이터 비과금에 대한 플랫폼사업자의 전략에 관한 연구: 사업기회 및 위기 관점에서)

  • Cho, Dae-Keun;Song, In-Kuk
    • Journal of Internet Computing and Services
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    • v.18 no.5
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    • pp.123-131
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    • 2017
  • With the rapid growth of mobile services, the various charging methods for mobile data have emerged in the mobile service market. Among them, network operators have begun to provide the zero-rating without any extra charge for the data that use the specific mobile application & services. Zero-rating, the free mobile data services by the network operators provoked many platform operators to confront business opportunity and risk. Though the platform operators are in urgent need of the strategy planning that considers business environments, any research endeavors explaining zero-rating and platform does not exist. Moreover, the analyses of potential effects of zero-rating on the business acts of platform operators has not been performed. Therefore, the study aims to identify the potential business opportunity and risk to prepare the various strategic countermeasure in platform operators' shoes. The study might enable the researchers to properly understand zero-rating and platform, and be utilized as a reference in planning the business strategy of the platform operators.

Modeling and Selecting Optimal Features for Machine Learning Based Detections of Android Malwares (머신러닝 기반 안드로이드 모바일 악성 앱의 최적 특징점 선정 및 모델링 방안 제안)

  • Lee, Kye Woong;Oh, Seung Taek;Yoon, Young
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.11
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    • pp.427-432
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    • 2019
  • In this paper, we propose three approaches to modeling Android malware. The first method involves human security experts for meticulously selecting feature sets. With the second approach, we choose 300 features with the highest importance among the top 99% features in terms of occurrence rate. The third approach is to combine multiple models and identify malware through weighted voting. In addition, we applied a novel method of eliminating permission information which used to be regarded as a critical factor for distinguishing malware. With our carefully generated feature sets and the weighted voting by the ensemble algorithm, we were able to reach the highest malware detection accuracy of 97.8%. We also verified that discarding the permission information lead to the improvement in terms of false positive and false negative rates.

Comparative Analysis of ViSCa Platform-based Mobile Payment Service with other Cases (스마트카드 가상화(ViSCa) 플랫폼 기반 모바일 결제 서비스 제안 및 타 사례와의 비교분석)

  • Lee, June-Yeop;Lee, Kyoung-Jun
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.163-178
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    • 2014
  • Following research proposes "Virtualization of Smart Cards (ViSCa)" which is a security system that aims to provide a multi-device platform for the deployment of services that require a strong security protocol, both for the access & authentication and execution of its applications and focuses on analyzing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service by comparing with other similar cases. At the present day, the appearance of new ICT, the diffusion of new user devices (such as smartphones, tablet PC, and so on) and the growth of internet penetration rate are creating many world-shaking services yet in the most of these applications' private information has to be shared, which means that security breaches and illegal access to that information are real threats that have to be solved. Also mobile payment service is, one of the innovative services, has same issues which are real threats for users because mobile payment service sometimes requires user identification, an authentication procedure and confidential data sharing. Thus, an extra layer of security is needed in their communication and execution protocols. The Virtualization of Smart Cards (ViSCa), concept is a holistic approach and centralized management for a security system that pursues to provide a ubiquitous multi-device platform for the arrangement of mobile payment services that demand a powerful security protocol, both for the access & authentication and execution of its applications. In this sense, Virtualization of Smart Cards (ViSCa) offers full interoperability and full access from any user device without any loss of security. The concept prevents possible attacks by third parties, guaranteeing the confidentiality of personal data, bank accounts or private financial information. The Virtualization of Smart Cards (ViSCa) concept is split in two different phases: the execution of the user authentication protocol on the user device and the cloud architecture that executes the secure application. Thus, the secure service access is guaranteed at anytime, anywhere and through any device supporting previously required security mechanisms. The security level is improved by using virtualization technology in the cloud. This virtualization technology is used terminal virtualization to virtualize smart card hardware and thrive to manage virtualized smart cards as a whole, through mobile cloud technology in Virtualization of Smart Cards (ViSCa) platform-based mobile payment service. This entire process is referred to as Smart Card as a Service (SCaaS). Virtualization of Smart Cards (ViSCa) platform-based mobile payment service virtualizes smart card, which is used as payment mean, and loads it in to the mobile cloud. Authentication takes place through application and helps log on to mobile cloud and chooses one of virtualized smart card as a payment method. To decide the scope of the research, which is comparing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service with other similar cases, we categorized the prior researches' mobile payment service groups into distinct feature and service type. Both groups store credit card's data in the mobile device and settle the payment process at the offline market. By the location where the electronic financial transaction information (data) is stored, the groups can be categorized into two main service types. First is "App Method" which loads the data in the server connected to the application. Second "Mobile Card Method" stores its data in the Integrated Circuit (IC) chip, which holds financial transaction data, which is inbuilt in the mobile device secure element (SE). Through prior researches on accept factors of mobile payment service and its market environment, we came up with six key factors of comparative analysis which are economic, generality, security, convenience(ease of use), applicability and efficiency. Within the chosen group, we compared and analyzed the selected cases and Virtualization of Smart Cards (ViSCa) platform-based mobile payment service.

Development of Android Smart Phone App for Analysis of Remote Sensing Images (위성영상정보 분석을 위한 안드로이드 스마트폰 앱 개발)

  • Kang, Sang-Goo;Lee, Ki-Won
    • Korean Journal of Remote Sensing
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    • v.26 no.5
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    • pp.561-570
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    • 2010
  • The purpose of this study is to develop an Android smartphone app providing analysis capabilities of remote sensing images, by using mobile browsing open sources of gvSIG, open source remote sensing software of OTB and open source DBMS of PostgreSQL. In this app, five kinds of remote sensing algorithms for filtering, segmentation, or classification are implemented, and the processed results are also stored and managed in image database to retrieve. Smartphone users can easily use their functions through graphical user interfaces of app which are internally linked to application server for image analysis processing and external DBMS. As well, a practical tiling method for smartphone environments is implemented to reduce delay time between user's requests and its processing server responses. Till now, most apps for remotely sensed image data sets are mainly concerned to image visualization, distinguished from this approach providing analysis capabilities. As the smartphone apps with remote sensing analysis functions for general users and experts are widely utilizing, remote sensing images are regarded as information resources being capable of producing actual mobile contents, not potential resources. It is expected that this study could trigger off the technological progresses and other unique attempts to develop the variety of smartphone apps for remote sensing images.

A Scheme for Identifying Malicious Applications Based on API Characteristics (API 특성 정보기반 악성 애플리케이션 식별 기법)

  • Cho, Taejoo;Kim, Hyunki;Lee, Junghwan;Jung, Moongyu;Yi, Jeong Hyun
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.1
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    • pp.187-196
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    • 2016
  • Android applications are inherently vulnerable to a repackaging attack such that malicious codes are easily inserted into an application and then resigned by the attacker. These days, it occurs often that such private or individual information is leaked. In principle, all Android applications are composed of user defined methods and APIs. As well as accessing to resources on platform, APIs play a role as a practical functional feature, and user defined methods play a role as a feature by using APIs. In this paper we propose a scheme to analyze sensitive APIs mostly used in malicious applications in terms of how malicious applications operate and which API they use. Based on the characteristics of target APIs, we accumulate the knowledge on such APIs using a machine learning scheme based on Naive Bayes algorithm. Resulting from the learned results, we are able to provide fine-grained numeric score on the degree of vulnerabilities of mobile applications. In doing so, we expect the proposed scheme will help mobile application developers identify the security level of applications in advance.

On Developments of Teaching-Learning Contents and Constructivist Teaching Methods Using Mobile Applications Based on Augmented Reality in Mathematics Education (증강현실 기반 모바일 앱을 활용한 수학 교수·학습 콘텐츠 개발과 구성주의적 수업방안)

  • Kim, Byung Hak;Song, Jinsu;Park, Ye Eun;Jang, Yo Han;Jeong, Young Hun;Ahn, Jin Hee;Kim, Jun Hyuk;Go, Eunryeong;Jang, In Kyung
    • Communications of Mathematical Education
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    • v.33 no.3
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    • pp.207-229
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    • 2019
  • In the era of the Fourth Industrial Revolution, various attempts have been made to incorporate ICT technology into mathematics teaching and learning, and the necessity and efficiency of classroom instruction using flipped learning, virtual reality and augmented reality have attracted attention. This leads to an increase in demand for instructional contents and their use in education. Therefore, there is a growing need for the development of instructional contents that can be applied in the field and the study of teaching methods. In this point of view, this research classifies the types of teaching-learning, presents the flipped learning instruction and mathematics contents by teaching-learning types using constructivist mathematics education principles and augmented reality-based mobile applications. These methods and lesson plans can provide a useful framework for teaching-learning in mathematics education.

A Survey of Fraud Detection Research based on Transaction Analysis and Data Mining Technique (결제로그 분석 및 데이터 마이닝을 이용한 이상거래 탐지 연구 조사)

  • Jeong, Seong Hoon;Kim, Hana;Shin, Youngsang;Lee, Taejin;Kim, Huy Kang
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.6
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    • pp.1525-1540
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    • 2015
  • Due to a rapid advancement in the electronic commerce technology, the payment method varies from cash to electronic settlement such as credit card, mobile payment and mobile application card. Therefore, financial fraud is increasing notably for a purpose of personal gain. In response, financial companies are building the FDS (Fraud Detection System) to protect consumers from fraudulent transactions. The one of the goals of FDS is identifying the fraudulent transaction with high accuracy by analyzing transaction data and personal information in real-time. Data mining techniques are providing great aid in financial accounting fraud detection, so it have been applied most extensively to provide primary solutions to the problems. In this paper, we try to provide an overview of the research on data mining based fraud detection. Also, we classify researches under few criteria such as data set, data mining algorithm and viewpoint of research.