• Journal of Korea Game Society
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• v.12 no.5
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• pp.35-42
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• 2012

Main focus of FPS game's play is securing vantage points in space based on specific theme and removing enemies. It could be more directly interacted with players' game space than other genres. This paper analyzes design patterns on FPS game of nine types consisted of three themes : past war, modern war, near future war, which is based on 10 different patterns of near future theme-oriented by Hullett and Whitehead. As an outcome, an important function of 'element of cover' was found additionally as a main pattern besides the 10 different patterns. And by analyzing its attributes, it is suggested the efficient way to use the 'cover' pattern for level-design. This result can be utilized as an empirical guideline for level-design of FPS games by theme.

• Journal of Korea Game Society
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• v.16 no.4
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• pp.35-44
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• 2016

To apply the player's experiences to the design process of the game levels set by the developer, gameplay behavior analysis is needed. The player's behavior which is different by how much he got experiences from the play has generally been studied by one computational approach based on numerical data and the other HCI(human-computer interaction) approach through heuristic analysis. For the analysis of the player's behavior with the level design patterns in FPS(first-person shooter) games, in this paper those methods are used to code 12 main types of action, which in turn is simply categorized into 5 kinds of behavior pattern. Along with it, an optimized visualization is proposed to intuitively compare the flow of behavior pattern with the time of playing game.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2866-2879
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• 2012

Among the various security threats in online games, the use of game bots is the most serious problem. Previous studies on game bot detection have proposed many methods to find out discriminable behaviors of bots from humans based on the fact that a bot's playing pattern is different from that of a human. In this paper, we look at the chatting data that reflects gamers' communication patterns and propose a communication pattern analysis framework for online game bot detection. In massive multi-user online role playing games (MMORPGs), game bots use chatting message in a different way from normal users. We derive four features; a network feature, a descriptive feature, a diversity feature and a text feature. To measure the diversity of communication patterns, we propose lightly summarized indices, which are computationally inexpensive and intuitive. For text features, we derive lexical, syntactic and semantic features from chatting contents using text mining techniques. To build the learning model for game bot detection, we test and compare three classification models: the random forest, logistic regression and lazy learning. We apply the proposed framework to AION operated by NCsoft, a leading online game company in Korea. As a result of our experiments, we found that the random forest outperforms the logistic regression and lazy learning. The model that employs the entire feature sets gives the highest performance with a precision value of 0.893 and a recall value of 0.965.

• Journal of Korea Multimedia Society
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• v.10 no.8
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• pp.1060-1067
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• 2007

We need various methods to develop MMORPG that is game genre which many users use among various game genre using Internet. Specially, to heighten efficiency of distributing work, Object-oriented language such as C++ is used and we need design techniques that can take advantage of enough object-oriented concept when making large-scale game. There is various pattern that can apply in software breakup design in GoF's design pattern for these design techniques. If you apply Observer pattern to Party System Design for forming community between game users, you can easily add new class and maintain system later. Party Play is one of the important system that is used to form game users' community in MMORPG games. The main point that must be considered in Party-Play-System is to divide evenly experience value and acquisition that is got by Party-Play among users according to each user's level. To implement Party Play System that consider maintenance of system, in this paper, we propose a method using GoF's Observer-Pattern, showing you that proposed method which has advantage to dynamic memory allocation and to virtual method call can be used usefully to change object to real time at program run and to add new class and to maintain system new.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.117-125
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• 2009

This paper describes the result of applying neuro-fuzzy reasoning, which conducts Go term knowledge based on pattern knowledge, to the opening game of Go. We discuss the implementation of neuro-fuzzy reasoning for deciding the best next move to proceed through the opening game. We also let neuro-fuzzy reasoning play against TD($\lambda$) learning to test the performance. The experimental result reveals that even the simple neuro-fuzzy reasoning model can compete against TD($\lambda$) learning and it shows great potential to be applied to the real game of Go.

• Journal of Korea Game Society
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• v.16 no.2
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• pp.7-16
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• 2016

In this paper, we propose a method for effectively detecting specific behavior. The proposed method detects outlying behavior based on the game players' characteristics. These characteristics are captured non-invasively in a general game environment and add keystroke based on repeated pattern. In this paper, cameras were used to analyze observed data such as facial expressions and player movements. Moreover, multimodal data from the game players was used to analyze high-dimensional game-player data for a detection effect of repeated behaviour pattern. A support vector machine was used to efficiently detect outlying behaviors. We verified the effectiveness of the proposed method using games from several genres. The recall rate of the outlying behavior pre-identified by industry experts was approximately 70%. In addition, Repeated behaviour pattern can be analysed possible. The proposed method can also be used for feedback and quantification about analysis of various interactive content provided in PC environments.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.95-107
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• 2012

Communication skill to maintain personal relationships is a crucial factor in our social life. However, even though a number of people are experiencing difficulty in communication owing to their poor interpersonal interchanges in real life, they are interacting with virtual characters in artificially created virtual space. In order to remedy such a lack of communication among game players, first, they need to search appropriate ways to communicate each other in real life, but not in virtual space, or to create a game space as a new place for interaction among them by utilizing advantages of the game world. To accomplish such an aim, it is necessary to precede the research on what kind of relations or characteristics for game players' interaction to others in the real life and game world. For the reason, in this paper, we investigate interaction patterns of game players in real life and in the virtual space. In order to perform this investigation, an ego-gram, which demonstrates the pattern of the ego states as a field-oriented approach is used as the research method. The result shows that there are differences between patterns in each spaces. so, we apply a factor analysis and analyse the relationship between the transaction pattern of players in two spaces using the ego-gram.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.422-427
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• 2010

Korean Game industry, especially MMORPG(Massively Multiplayer Online Game) has been rapidly expanding in these days. But As game industry is growing, lots of online game security incidents have also been increasing and getting prevailing. One of the most critical security incidents is 'Game Bots', which are programs to play MMORPG instead of human players. If player let the game bots play for them, they can get a lot of benefic game elements (experience points, items, etc.) without any effort, and it is considered unfair to other players. Plenty of game companies try to prevent bots, but it does not work well. In this paper, we propose a behavior pattern model for detecting bots. We analyzed behaviors of human players as well as bots and identified six game features to build the model to differentiate game bots from human players. Based on these features, we made a Naive Bayesian classifier to reasoning the game bot or not. To evaluated our method, we used 10 game bot data and 6 human Player data. As a result, we classify Game bot and human player with 88% accuracy.

• Journal of Korea Game Society
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• v.16 no.3
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• pp.27-34
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• 2016

New game systems have emerged with the rapid growth of Korea smartphone game industry. Especially auto battle system introduced in RPG which is the most popular genre, which has brought a significant change in the understanding of the computer games. To understand this change, it is necessary to look at what circumstances did emerge auto battle system. What is important here is the smart phone as the technical apparatus which defines the presence of a smart phone game, and the use pattern of the smart phone. the technical device and Its use pattern are affecting the activity of the user how to play the game, game developers are to create the game system according to this play style. By examining the appearance and growth of this auto battle system, we can confirm that the micro changes in the game system, reflect changes in the present form of a computer game. This fact will widen the understanding of the history of computer games.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.627-637
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• 2015

As game item trading becomes more popular with the rapid growth of online game market, the market for trading game items by cash has increased up to KRW 1.6 trillion. Thanks to this active market, it has been easy to turn these items and game money into real money. As a result, some malicious users have often attempted to steal other players' rare and valuable game items by using their account. Therefore, this study proposes a detection model through analysis on these account thieves' behavior in the Massive Multiuser Online Role Playing Game(MMORPG). In case of online game identity theft, the thieves engage in economic activities only with a goal of stealing game items and game money. In this pattern are found particular sequences such as item production, item sales and acquisition of game money. Based on this pattern, this study proposes a detection model. This detection model-based classification revealed 86 percent of accuracy. In addition, trading patterns when online game identity was stolen were analyzed in this study.