• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.157-163
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• 2022

As the online game market grows, the use of game bots is causing the most serious problem for game services. We propose a harvest coordinate analysis model to detect harvesting bots among game bots of the Massively Multiplayer Online Role-Playing Games(MMORPGs) genre. The proposed model analyzes the player's harvesting behavior using the coordinate data. Game bots can obtain in-game goods and items more easily than normal players and are not affected by realistic restrictions such as sleep time and character manipulation fatigue. As a result, there is a difference in harvesting coordinates between normal players and game bots. We divided the coordinate zones and used these coordinate zone differences to distinguish between game bot players and normal players. We created a dataset with NCSoft's AION log and applied it to a random forest model to detect game bots, and as a result, we derived performance with a recall of 0.72 and a precision of 0.92.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1131-1141
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• 2015

In this paper, we proposed a new approach of machine learning based method for detecting game-bots from normal players in MMORPG by inspecting the player's action log data especially in-game money increasing/decreasing event log data. DBSCAN (Density Based Spatial Clustering of Applications with Noise), an one of density based clustering algorithms, is used to extract the attributes of spatial characteristics of each players such as a number of clusters, a ratio of core points, member points and noise points. Most of all, even game-bot developers know principles of this detection system, they cannot avoid the system because moving a wide area to hunt the monster is very inefficient and unproductive. As the result, game-bots show definite differences from normal players in spatial characteristics such as very low ratio, less than 5%, of noise points while normal player's ratio of noise points is high. In experiments on real action log data of MMORPG, our game-bot detection system shows a good performance with high game-bot detection accuracy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1153-1160
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• 2018

As the number of online game users increases and the market size grows, various kinds of cheating are occurring. Game bots are a typical illegal program that ensures playtime and facilitates account leveling and acquisition of various goods. In this study, we propose a method to detect game bots based on user action time interval (ATI). This technique observes the behavior of the bot in the game and selects the most frequent actions. We distinguish between normal users and game bots by applying Machine Learning to feature frequency, ATI average, and ATI standard deviation for each selected action. In order to verify the effectiveness of the proposed technique, we measured the performance using the actual log of the 'Aion' game and showed an accuracy of 97%. This method can be applied to various games because it can utilize all actions of users as well as character movements and social actions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.585-600
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• 2012

Security issues in online games are increasing as the online game industry grows. Real money trading (RMT) by online game users has become a security issue in several countries including Korea because RMT is related to criminal activities such as money laundering or tax evasion. RMT-related activities are done by professional work forces, namely gold-farmers, and many of them employ the automated program, bot, to gain cyber asset in a quick and efficient way. Online game companies try to prevent the activities of gold-farmers using game bots detection algorithm and block their accounts or IP addresses. However, game bot detection algorithm can detect a part of gold-farmer's network and IP address blocking also can be detoured easily by using the virtual private server or IP spoofing. In this paper, we propose a method to detect gold-farmer groups by analyzing their connection patterns to the online game servers, particularly information on their routing and source locations. We verified that the proposed method can reveal gold-farmers' group effectively by analyzing real data from the famous MMORPG.

• Journal of Korea Game Society
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• v.15 no.3
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• pp.51-62
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• 2015

Do artifacts function merely as tools? Today tremendous softwares work to assist or guide their users. This paper will apply the theories of Science & Technology Studies(STS) and the agent definition of Floridi & Sanders(2004) to game-bot programmes. Consequently we would see game-bots have had the interactivity, autonomy and adaptability. They are the position of agents even in playing. Further they may be companion relationship in the way that bots and human players compose each other. Then we will be induce to new question, the bots may be political-social. While human actors in computer based rule are the compounds being affected by the artificials, they will be never same to classic human actors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1077-1084
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• 2015

Security issues such as an illegal acquisition of personal information and identity theft happen due to using game bots in online games. Game bots collect items and money unfairly, so in-game contents are rapidly depleted, and honest users feel deprived. It causes a downturn in the game market. In this paper, we defined the growth types by analyzing the growth processes of users with actual game data. We proposed the framework that classify hard-core users and game bots in the growth patterns. We applied the framework in the actual data. As a result, we classified five growth types and detected game bots from hard-core users with 93% precision. Earlier studies show that hard-core users are also detected as a bot. We clearly separated game bots and hard-core users before full growth.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.849-861
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• 2015

As the rise in popularity of online games, the users start exchanging rare items for real money. As RMT (Real Money Trade) is prevalent, GFG (Gold Farming Group) who abuse RMT shows up. GFG causes social problems such as identity theft, privacy leaks. Because they needs many bot characters to gather game items. In addition, GFG induce RMT that makes in-game problems such as a destroying game economy, account hacking. Therefore, It is very important work to collapse GFG at the perspective of social and in-game. In this paper, we proposed a fundamental method for detecting RMT buyers for the collapse of GFG at the perspective of buyer by Law of Demand and Supply. We found two type of RMT by analyzing actual game data and detected RMT buyers with high recall ratio of 98% by ruled-based detection.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.293-308
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• 2011

The preliminary security assessment is an information security process to analyze security weaknesses before beginning of services. Discovering security weakness through preliminary security assessment is highly required because it costs much when security incident occur in the middle of service operation. However, this assessment is not widely spread in the online game service domain yet. In this paper, we summarize the security risk existed in the online game service, and we classify the security requirements related to the each risk. Also, through the case study, we evaluated the effectiveness of preliminary security assessment in this domain. In addition, we suggest checklists that should be reviewed once in game-client side, network-side and game-server side for the purpose of security enhancement.

• Journal of the Korea Convergence Society
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• v.7 no.3
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• pp.143-148
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• 2016

This paper analyses the main aspects the aspects of the Third-person shooting game and then investigates the released TPS games which are integrated with Role-playing game types of genres. Then we propose the technical points in designing and developing of the integrated action games to increase the immersion in playing the games. Also we propose the artifice in order to cut down the cost and enhance the portability to the mobile platform.

• Journal of Korea Game Society
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• v.21 no.6
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• pp.87-96
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• 2021

As the industry develops, the technology used for games is also being advanced. In particular, AI technology is used to game automation and intelligence. These game player patterns are widely used in online games such as player matchmaking, generation of friendly or hostile NPCs, and balancing of game worlds. This study proposes a model generation method for game players. For model generation, attributes such as hunting, collection, movement, combat, crisis management, production, and interaction were defined, and patterns were extracted and modeled using decision tree method. To evaluate the proposed method, we used the game log of a commercial game and confirmed the meaningful results.