• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1426-1447
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• 2021

The payoff game between task publishers and users in the mobile crowdsensing environment is a hot topic of research. A optimal payoff selection model based on stochastic evolutionary game is proposed. Firstly, the process of payoff optimization selection is modeled as a task publisher-user stochastic evolutionary game model. Secondly, the low-quality data is identified by the data quality evaluation algorithm, which improves the fitness of perceptual task matching target users, so that task publishers and users can obtain the optimal payoff at the current moment. Finally, by solving the stability strategy and analyzing the stability of the model, the optimal payoff strategy is obtained under different intensity of random interference and different initial state. The simulation results show that, in the aspect of data quality evaluation, compared with BP detection method and SVM detection method, the accuracy of anomaly data detection of the proposed model is improved by 8.1% and 0.5% respectively, and the accuracy of data classification is improved by 59.2% and 32.2% respectively. In the aspect of the optimal payoff strategy selection, it is verified that the proposed model can reasonably select the payoff strategy.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.243-248
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• 2021

Although many different types of covert channels have been suggested in the literature, there are little work in directly applying game theory to building up covert channel. This is because researchers have mainly focused on tailoring game theory for covert channel analysis, identification, and covert channel problem solving. Unlike typical adaptation of game theory to covert channel, we show that game theory can be utilized to establish a new type of covert channel in IoT devices. More specifically, we propose a covert channel that can be constructed by utilizing the Nash Equilibrium with sensor data collected from IoT devices. For covert channel construction, we set random seed to the value of sensor data and make payoff from random number created by running pseudo random number generator with the configured random seed. We generate I × J (I ≥ 2, J ≥ 2) matrix game with these generated payoffs and attempt to obtain the Nash Equilibrium. Covert channel construction method is distinctly determined in accordance with whether or not to acquire the Nash Equilibrium.

• Journal of Korea Game Society
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• v.9 no.1
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• pp.11-20
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• 2009

This study explores the effects of 'save and load' on game storytelling. In video games, a player can control the game she plays by repeatedly saving and loading game data until she reaches her intended goal. As a consequence, a player can manage the game time. In this article, game time is divided into two parts; play time and story time in order to examine how player's intentions are reflected in game storytelling. This is what distinguishes game narrative from others in that the player generates her own story by saving and loading.

• Journal of Korea Game Society
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• v.16 no.2
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• pp.61-74
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• 2016

As e-Sports evolves, a variety of industries grow together. Game broadcastings contribute to spread video game culture through various media platforms. Hence people start to perceive e-sports as a genre of sports and the demand on real-time game broadcasting increases. The global game broadcasting channels based on OTT(Over-The-Top) service also increase rapidly. In this paper we understand the status of streaming service and watching attitude of global game broadcasting. We also provide practical suggestions along with analysis results.

• ETRI Journal
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• v.35 no.6
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• pp.1058-1067
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• 2013

An approach for game bot detection in massively multiplayer online role-playing games (MMORPGs) based on the analysis of game playing behavior is proposed. Since MMORPGs are large-scale games, users can play in various ways. This variety in playing behavior makes it hard to detect game bots based on play behaviors. To cope with this problem, the proposed approach observes game playing behaviors of users and groups them by their behavioral similarities. Then, it develops a local bot detection model for each player group. Since the locally optimized models can more accurately detect game bots within each player group, the combination of those models brings about overall improvement. Behavioral features are selected and developed to accurately detect game bots with the low resolution data, considering common aspects of MMORPG playing. Through the experiment with the real data from a game currently in service, it is shown that the proposed local model approach yields more accurate results.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.3
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• pp.222-230
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• 2016

As the global game market has been more competitive, it has been important to analyze success factors of game products. In this paper, we applied a Bass Diffusion Model and Clustering Analysis to identify the success factors of games based on data from Steam, an international game platform. By using a diffusion model, we first categorize game products into two groups : successful and unsuccessful games. Then, each group has been analyzed by using clustering analysis based on product features such as genres, price, and minimum system requirements. As a result, success factors of a game have been identified. The result shows that customers in game industry appreciate sophisticated contents. Unlike many other industries, price is not considered as a key success factor in the game industry. Expecially, advanced independent video games (commonly referred to as indie games) with killer contents show competitiveness in the market.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.567-574
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• 2013

In this paper, we have proposed an architectural solution for a system for the visualization and modification of large amounts of data. The pattern is based on an asynchronous execution of programmable commands and a reflective approach of an object structure composition. The described pattern provides great flexibility, which helps adopting it easily to custom application needs. We have implemented a system based on the described pattern. The implemented system presents an innovative approach for a dynamic data object initialization and a flexible system for asynchronous interaction with data sources. We believe that this system can help software developers increase the quality and the production speed of their software products.

• Journal of Korea Game Society
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• v.10 no.6
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• pp.79-87
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• 2010

Through the development of digital technology digital game is becoming a fusion of work and play. The aim of this article is to define the concept of labortainment game that playing the game as a consumer is connected with work to create new value-added economic production and to ascertain the characteristics of labortainment game through a semiotic approach. Digital Game has evolved into a more advanced from which accumulated game data is used as something of value in itself for facilitating collaboration as well as entertainment value of games. Labortainment game fills game developer's hidden desire through using the game data produced by the collective amusements for external service.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.529-534
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• 2021

Computing thinking is regarded as one of the important skills required in the 21st century, and many countries have introduced and implemented computing thinking training courses. Among computational thinking education methods, educational game-based methods increase student participation and motivation, and increase access to computational thinking. Autothinking is an educational game developed for the purpose of providing computational thinking education to learners. It is an adaptive system that dynamically provides feedback to learners and automatically adjusts the difficulty according to the learner's computational thinking ability. However, because the game was designed based on rules, it cannot intelligently consider the computational thinking of learners or give feedback. In this study, game data collected through Autothikning is introduced, and game score prediction that reflects computational thinking is performed in order to increase the adaptability of the game by using it. To solve this problem, a comparative study was conducted on linear regression, decision tree, random forest, and support vector machine algorithms, which are most commonly used in regression problems. As a result of the study, the linear regression method showed the best performance in predicting game scores.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.67-81
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• 2008

Last decade, IT industry in Korea has been developed greatly. The game industry as an international leader has given good value added to its country. Game industry is one of the speedy improved one and it showed over 20% of growth rate from 2002. Most distressings in Game industry, there are no established costing system in spite that there should be in emerging market. In 2004, Game Contents Costing Model using Mission and Event was developed and also the study of Game Elements weight was done in 2005. The cost of Game Contents can be calculated by GEP and its unit price. The study of Game Contents Sizing Model was done in 2005. The costing of Game Contents by single Game Element which represents software which is one of 3 Game Elements-plan, graphic and software-and it is counted by mission and event. If the software element only can not well represent Game Contents volume, we can include plan and graphic elements for Game Contents costing. And we can say above two methods as a costing model of Game Contents. In this paper, these models were tested empirically and proved as usable.