• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1499-1506
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• 2017

The use of smartphones and the launch of various apps have increased exponentially, and malicious apps have also increased. Existing app recommendation systems have been limited to operate based on static information analysis such as ratings, comments, and popularity categories of other users who are online. In this paper, we first propose a robust app recommendation system that realistically uses dynamic information of apps actually used in smartphone and considers static information and dynamic information at the same time. In other words, this paper proposes a robust Android app recommendation system by partially reflecting the time of the app, the frequency of use of the app, the interaction between the app and the app, and the number of contact with the Android kernel. As a result of the performance evaluation, the proposed method proved to be a robust and efficient app recommendation system.

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

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.947-948
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• 2015

IOT(Internet of things) is a technology to embed various sensors and communication features on diverse things such as home appliances, mobile devices, wearable computers and connect to the Internet and through this technology, the status of things connected to the network can be analyzed and controlled with various data. On the other hand, this paper suggests to develop a merchandise management app using Android-based barcode to systematically manage expiry date of various goods that we purchase in our daily life. Therefore, individual goods are recognized with mobile-based barcode and divided under each category. By additionally supporting the notification service to let us know about expire date, goods can be efficiently managed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1491-1498
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• 2017

As the use of smartphones and the launch of various apps have increased rapidly, the number of malicious apps has also increased, and the damage is continuing. The Google Market where Android apps are registered is inevitably present at the same time as normal apps and malicious apps even though there are regulations for app registration. Especially, as social networks are activated, users are connected with social networks, and the ratings, downloads and awareness information are reflected in the number of downloaded apps. As a result, when users choose their apps by simply reflecting ratings, popularity, popular comments, and highly-categorized apps, malicious app downloads can sometimes cause significant harm. Therefore, this study first analyzed the tendency of malicious apps by directly crawling and analyzing long-term social information in the currently active Android market.

• Knowledge Management Research
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• v.23 no.2
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• pp.37-60
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• 2022

The growth of virtual reality games and the popularization of blockchain technology are bringing significant changes to the formation of the metaverse industry ecosystem. Especially, after Meta acquired Oculus, a VR device and application company, the growth of VR-based metaverse services is accelerating. In this study, the concept that supports leisure activities in the metaverse environment is explored realting to game-like features in VR apps, which differentiates traditional mobile apps based on a smart phone device. Using exploratory text mining methods and network analysis approches, 241 apps registed in the Oculus Quest 2 App Store were analyzed. Analysis results from a quasi-network show that a leisure concept is closely related to various genre features including a game and tourism. Additionally, the anlaysis results of G & F model indicate that the leisure concept is distictive in the view of gateway brokerage role. Those results were also confirmed in LDA topic modeling analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.379-386
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• 2014

As the use of mobile device is increasing rapidly, the number of users is also increasing. However, most of the app stores are using recommendation of simple ranking method, so the accuracy of recommendation is lower. To recommend an item that is more appropriate to the user, this paper proposes a technique that reflects the weight of user information and recent preference degree of item. The proposed technique classifies the data set by categories and then derives a predicted value by applying the user's information weight to the collaborative filtering technique. To reflect the recent preference degree of item by categories, the average of items' rating values in the designated period is computed. An item is recommended by combining the two result values. The experiment result indicated that the proposed method has been more enhanced the accuracy, appropriacy, compared to item-based, user-based method.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.429-437
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• 2014

Product promotion App is developed using an interactive video in order to overcome the existing ATL marketing limitations and to respond to target age groups and lifestyle changes. The product promotion App which is positioned as a smart care center by analyzing customer needs with the Customer Journey Map, is comprised of 3 categories such as interest, information and management reflecting media characteristics of smart mobile contents. It intends to induce viral promotions with comical and interactive alopecia simulator directly described by a specialist doctor which ensures reliability of products. In addition, it is made for customers to continuously manage the alopecia through management tools, and company can expect an effect of being used as a core tool for marketing activities by offering promotional information along with product feedbacks.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.467-472
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• 2021

본 연구는 패션앱 후기글에 나타나는 구매자의 의견에 대한 '평가분석(Evaluation Analysis: EA)'을 수행하여, 이를 기반으로 상품의 검색 및 추천을 수행하는 의류 검색추천 챗봇을 개발하는 LICO 프로젝트의 언어데이터 구축의 일환으로 수행되었다. '평가분석 트리플(EAT)'과 '평가기반요청 쿼드러플(EARQ)'의 구성요소들에 대한 주석작업은, 도메인 특화된 단일형 핵심어휘와 다단어(MWE) 핵심패턴들을 FST 방식으로 구조화하는 DECO-LGG 언어자원에 기반하여 반자동 언어데이터 증강(SSP) 방식을 통해 진행되었다. 이 과정을 통해 20여만 건의 후기글 문서(230만 어절)로 구성된 EVAD 평가주석데이터셋이 생성되었다. 여성의류 도메인의 평가분석을 위한 '평가속성(ASPECT)' 성분으로 14가지 유형이 분류되었고, 각 '평가속성'에 연동된 '평가내용(VALUE)' 쌍으로 전체 35가지의 {ASPECT-VALUE} 카테고리가 분류되었다. 본 연구에서 구축된 EVAD 평가주석 데이터의 성능을 평가한 결과, F1-Score 0.91의 성능 평가를 획득하였으며, 이를 통해 향후 다른 도메인으로의 확장된 적용 가능성이 유효함을 확인하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.323-326
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• 2011

스마트기기가 많은 부분에서 쓰임에 따라 의료 부분에서 스마트기기용 앱이 사용 할 수 있게 되었다. 의료용 앱이라고 하여 이 앱을 사용함으로서 의료인은 진료에 도움이 될 수 있고, 일반인들은 자신의 건강을 관리 할 수 있게 되었다. 의료용 앱의 정의에 따라 스마트기기 부분 대하여 사용 될 수 있는 시스템이 있는데, 그것은 바로 CDSS이다. 임상 의사 결정 지원 시스템이라고 하며, 의료인들이 의료 결정을 할 때 도움을 주는 시스템이다. 이것은 HL7(Health Level 7) 표준이며, 국제 표준인 Arden Syntax로 표현 할 수 있다. 그리고 크게 3가지의 카테고리로 이루어져 있으며 각각 부분에서 의료 진료에 관한 내용을 표현한다. 또한 시스템간의 XML로 교환하여 사용 할 수 있다. 하지만 스마트기기는 그 자체의 기능과 성능으로 CDSS 서비스를 하기에는 많이 부족하다. 이 부족한 점은 모바일 클라우드를 사용한다면 의료용 앱의 완성도와 신뢰성이 더 높아 질 것이다. 의료인들이 이러한 의료용 앱을 사용함으로써 환자 진료에 많은 도움이 될 수 있을 것이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1169-1172
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• 2013

모바일 단말기들이 기술적으로 발달하면서 모바일 앱 시장도 급속도로 성장하고 있다. 모바일 앱중에서도 메신저, 커뮤니케이션 앱들의 시장 점유율이 현저하게 높은 실정인데 반해 해당 앱들에 서 사용되는 비속어, 은어에 대한 제제는 전무하다. 현재 정부차원에서도 모바일 앱에서 행해지는 무분별한 언어폭력에 대한 조치를 취하려는 모습을 보인다는 것을 볼 때 메신저, 커뮤니케이션 모바일 앱에서 사용될 필터링 시스템은 선택이 아닌 필수라고 볼 수 있다. 따라서 이 논문에서는 안드로이드 플랫폼 기반 모바일 앱에서 SQLite를 활용한 앱의 내부 DB를 분석하여 비속어와 같은 특정 카테고리의 단어 사용빈도가 일정횟수 이상이 되면 사용자에게 경고 메시지를 보내주는 시스템을 제안한다.