• Journal of Korea Game Society
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• v.15 no.3
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• pp.177-188
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• 2015

In-game cheating by the use of unauthorized software programs has always been a big problem that they can damage in First Person Shooting games, although companies operate a variety of client security solutions in order to prevent games from the cheating attempts. This paper proposes a method for detecting cheaters in FPS games by using game log analysis in a server-side. To accomplish this, we did a comparative analysis of characteristics between cheaters and general users focused on commonly loaded logs in the game. We proposed a cheating detection model by using artificial neural network algorithm. In addition, we did the performance evaluation of the proposed model by using the real dataset used in business.

• Journal of Korea Game Society
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• v.20 no.4
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• pp.89-100
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• 2020

The purpose of this study is to identify online-game players' desire in cheating programs through Rene Girard's theory of mimetic desire. Cheating programs disrupts the magic circle of the game with denying the lusory attitude that players should have. The cheating players' desires do not go directly to victory, but are mediated by a virtual 'model player' which the rules of the game imply. They are internally mediated, so there is constant conflict in the play. Cheating players' desire to enhance skills by technology is defined as a false desire for transhuman.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.81-91
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• 2011

Hacking tools are evolving along the growth of on-line game industry. Those tools allow users with no programming knowledge to hack the game, which causes a lot of problems in on-line game services. Specifically, FPS games based on peer-to-peer networks are vulnerable to hacks. This paper analyzes cheating patterns by the case of Point Blank in Indonesia and prioritize countermeasures, which helps game companies handle hacks efficiently.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1465-1475
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• 2015

Cheating detection models in the online games can be divided into two parts. The one is on client based model, which is designed to detect malicious programs not to be run while playing the games. The other one is server based model, which distinguishes the difference between benign users and cheaters by the server log analysis. The client based model provides various features to prevent games from cheating, For instance, Anti-reversing, memory manipulation and so on. However, being deployed and operated on the client side is a huge weak point as cheaters can analyze and bypass the detection features. That Is why the server based model is an emerging way to detect cheating users in online games. But the simple log data such as FPS's one can be hard to find validate difference between two of them. In this paper, In order to compensate for the disadvantages of the two detection model above, We use the existing game security solution log as well as the server one to bring high performance as well as detection ratio compared to the existing detection models in the market.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.222-223
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• 2023

글로벌 게임 시장 규모가 2023년까지 2,000억 달러를 넘게 성장할 것이라는 전망과 대중적인 온라인 FPS(First Person Shooter) 게임들이 출시되면서 게임 내 치팅(Cheating) 도구들을 배포, 판매하는 사례가 등장하고 있다. 이러한 사례들은 게임 이용에 불편을 초래하고 게임 매출액 감소로 이어질 수 있다. 따라서 본 논문에서는 과거 FPS 게임들에 사용되었던 AimBot들의 사례와 악성코드 탐지에 사용되었던 연구 사례들을 분석해 메모리 변조를 사용하는 AimBot의 탐지 방안을 연구하였다.

• Journal of Korea Game Society
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• v.21 no.2
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• pp.3-16
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• 2021

This study examined to the aspects of capital and class structure, focusing on 'Reproduction' of Bourdieu, P, through collecting the post titles of the game community of online FPS games 'Overwatch' and 'Battleground', related to keyword, 'Game Hack'. The data used in the study was collected and refined through the statistical program R and analyzed by the analysis site 'Bigkinds'. At results, we will reveal that the class structure of the online FPS gamer group is based on cultural capital and reproduction, and suggest the right direction for the Game Hack regulation policy from the point of view of the cultural capital theory.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.261-264
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• 2004

컴퓨터 전략 시뮬레이션 게임 설계에서는 Master ADU(Artificial Decision Unit)의 전략 수립을 위한 방법으로 다양한 기법들이 연구되고 있다. 특히 한정된 자원 하에서 게임을 사실적이고 지적인 기능을 구현하기 위해 치팅(Cheating)을 활용하거나 간단한 인공지능 기법이 적용되고 있다. 하지만 이 기법들은 사용자 적응성 및 전략 수립의 단순성을 야기하는 단점을 가지고 있다. 본 연구에서는 전략 시뮬레이션 게임의 전략 수립 에이전트인 Master ADU(Artificial Decision Unit)를 위하여 셀룰라 오토마타의 초기 규칙 생성에 유전자 알고리즘의 교배 및 돌연변이, 적합도 평가를 거친 유전자 형을 적용한 혼합형 전략 수립 기법을 제안한다 이 기법은 ADU가 적합한 유전자 형을 생산 및 선택하여 사용자에 대해 적극적으로 학습할 수 있었다.

• Journal of Korea Game Society
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• v.16 no.1
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• pp.83-92
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• 2016

An online game is a huge distributed system comprised of servers and untrusted clients. In such circumstances, cheaters may employ abnormal behaviors through client modification or network packet tampering. Client-side detection methods have the merit of distributing the burden to clients but can easily be breached. In the other hand, server-side detection methods are trustworthy but consume tremendous amount of resources. Therefore, this paper proposes a security reinforcement method which involves both the client and the server. This method is expected to provide meaningful security fortification while minimizing server-side stress.