• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.123-129
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• 2021

MZ Generation has multipersona and characteristics that create various egos depending on the situation, and fashion styling is also expressed differently by each persona. Thus, this study investigates how to provide a multipersona or characteristic user experience to fashion shopping applications. Traditional fashion shopping apps, which focus on items, colors, and advertisements, have difficulty solving the problems of MZ generation fashion, so it is necessary to actively utilize their characteristics. We investigate the definitions and characteristics of multipersona and generation MZ, and identify the shopping behavior of generation MZ through prior research. We also analyze cases and improvements that indirectly utilize multipersona in fashion shopping apps. Four UX elements were derived through user interviews to identify needs and It was possible to derive positive effects, such as providing a shopping experience by forming one's own fashion characters in a personalized fashion beyond the existing fashion recommendation frame, which helps to worry about styling and gives a different experience.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.58-73
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• 2022

The purpose of this study is to construct a predictable estimation model that reflects the relationship between the variables of mobile app performance and to verify how app reviews affect app performance. In study 1 and 2, the relationship between app performance indicators was derived using correlation analysis and random forest regression estimation of machine learning, and app performance estimation modeling was performed. In study 3, sentiment scores for app reviews were by using sentiment analysis of text mining, and it was found that app review sentiment scores have an effect one lag ahead of the number of daily installations of apps when using multivariate time series analysis. By analyzing the dissatisfaction and needs raised by app performance indicators and reviews of apps, companies can improve their apps in a timely manner and derive the timing and direction of marketing promotions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.111-117
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• 2012

With the rapid growth of smart phone technologies, mobile user's demands for using services provided by existing web or portal cites are highly increased. These services, however, are designed for the environment of desktop PCs or laptops in general, so it requires lots of costs for corrections and has difficulties for system protection to use in current mobile devices. In this paper, we design and implement a middleware for android-based smart phone apps to cooperate with a portal system with minimum corrections and function configuration. Our middleware system is working as an interface between an existing portal system and mobile devices to provide harmonious usage and safe system protection.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.91-99
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• 2016

A security system in Android OS adopts sandbox and an permission model. In particular, the permission model operates the confirmation of installation time and all-or-nothing policy. Accordingly, the Android OS requires a user agreement for permission when installing an application, however there is very low level of user awareness for the permission. In this paper, the current status of permission requirement within mobile apps will be discovered, and the key inspection list with an appropriate method, when a mobile service provider autonomously inspects the violation of least privilege around financial companies, and its usefulness will be explored.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.5
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• pp.741-757
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• 2021

In addition to direct sales to consumers, the direct-to-consumers (D2C) strategy, which provides specialized experiences and services, communicates closely with a consumer's perspective. This tendency is related to the recent trend wherein the luxury fashion system is being transformed into a new luxury. Therefore, this study analyzes the development of online D2C platforms and investigates the characteristics of new luxury from the functional, symbolic, and experiential dimension perspectives based on mobile apps, which is becoming increasingly important among online D2C platforms. Based on the study results, the premium of new luxury fashion displayed in Louis Vuitton's mobile D2C platform in terms of product utility and functionality is newly defined as a usable luxury experience. Moreover, from the heritage perspective, based on the cultural sympathy of the brand contents, we determine that an attachment can be formed between new luxury fashion consumers and brands. Additionally, the personalization service and experiential content on the D2C platform can directly afford emotional and bonding induced brand immersion in a playful way.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.41-50
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• 2021

Many game and financial apps have emulator detection functionality to defend against dynamic reverse engineering attacks. However, existing Android emulator detection methods have limitations in detecting the latest mobile game emulators that are similar to actual devices. Therefore, in this paper, we propose a method to effectively detect Android emulators for mobile games based on Houdini module and strings of a library. The proposed method detects the two emulators, Nox and LD Player through specific strings included in libc.so of bionic, and an analysis of the system call execution process and memory mapping associated with the Houdini module.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.111-128
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• 2018

About 3.9 million apps and 24 primary categories can be approved on Apple iTunes Store. Making accurate categorization can potentially receive many benefits for developers, app stores, and users, such as improving discoverability and receiving long-term revenue. However, current categorization problems may cause usage inefficiency and confusion, especially for cross-attribution, etc. This study focused on evaluating the reliability of app categorization on Apple iTunes Store by using several rounds of inter-rater reliability statistics, locating categorization problems based on Machine Learning, and making more accurate suggestions about representative functionality stems for each primary category. A mixed methods research was performed and total 4905 popular apps were observed. The original categorization was proved to be substantial reliable but need further improvement. The representative functionality stems for each category were identified. This paper may provide some fusion research experience and methodological suggestions in categorization research field and improve app store's categorization in discoverability.

• Journal of IKEEE
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• v.22 no.3
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• pp.693-699
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• 2018

CNN based object recognitions have reported splendid results. However, the recognition of mobile apps raises an interesting challenge that recognition performance of similar widgets is not consistent. In order to improve the performance, we propose a noble method utilizing relations between input widgets. The recognition process flows from the Faster R-CNN based recognition to enhancement using a relation recognizer. The relations are represented as vector translation between objects in a relation space. Experiments on 323 apps show that our method significantly enhances the Faster R-CNN only approach.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.1
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• pp.9-16
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• 2019

Smartphones are becoming a portable computer. As a result, even the most sensitive financial application services are now available anywhere on the smartphone. Compared to general PCs, smartphones communicate with external devices through various channels such as wireless internet, mobile communication network, Bluetooth, and NFC, and a wide variety of applications are provided. Therefore, if vulnerabilities exist, the possibility of attack damage increases. In this paper, we analyze the vulnerabilities of dynamic virtual keyboards used in login of banking apps of smartphones with various physical constraints and propose countermeasures.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.121-131
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• 2022

We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.