Detection of MMORPG bots based on behavior analysis
Detection of MMORPG bots based on behavior analysis
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DOI：
10.1145/1501750.1501770
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发表时间：
2008-12
期刊：
影响因子：
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通讯作者：
R. Thawonmas;Yoshitaka Kashifuji;Kuan-Ta Chen
中科院分区：
文献类型：
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作者：
R. Thawonmas;Yoshitaka Kashifuji;Kuan-Ta Chen
游戏机器人，即，自动游戏客户端，目前正在给游戏发行商和大型多人在线角色扮演游戏（MMORPG）的真正玩家带来麻烦。游戏机器人的使用导致游戏平衡崩溃，玩家满意度下降，甚至退出游戏。为了防止这种情况，由真实的人类玩家或游戏大师扮演的游戏中的警察经常在游戏区域周围漫游并单独询问可疑的玩家，这显然是费力且无效的任务。与其他基于窗口事件（例如，游戏流量和CAPTCHA测试）的MMORPG游戏机器人自动检测工作相比，我们的研究重点是游戏发行商通常记录的日志，用于数据库回滚。特别是，我们的研究是基于人类和机器人角色之间日志中的动作频率和动作类型的差异。我们提出了由两个阶段组成的僵尸检测方法。在第一阶段中，如果一个未知角色的特定动作的频率比已知的人类角色高得多，则该角色将被归类为“机器人”。在第二阶段，其余的字符将被分类的支持向量机分类器基于他们的行动类型。我们评估所提出的方法，使用游戏日志的韩国MMORPG标题阴谋集团在线，并确认其有效性。
Game bots, i.e., autoplaying game clients, are currently causing troubles to both game publishers and bona fide players of Massively Multiplayer Online Role-Playing Games (MMORPGs). Use of game bots leads to collapse of game balance, decrease of player satisfaction, and even retirement from game. To prevent this, in-game polices, played by actual human players or game masters, often roam around game zones and individually question suspicious players, which is obviously laborious and ineffective task. In contrast to other work on automatic detection of MMORPG game bots based on the window events such as keystrokes, the game traffic, and the CAPTCHA test, our research focuses on log typically recorded by game publishers for database rollback. In particular, our research is based on discrepancies in action frequencies and action types in the log between human and bot characters. We propose the bot-detection methodology consisting of two stages. In the first stage an unknown character will be classified as "bot" if its frequencies of particular actions are much higher than those of known human characters. In the second stage, the rest of characters will be classified by the support vector machine classifier based on their action types. We evaluate the proposed methodology using game log of a Korean MMORPG titled Cabal Online and confirm its effectiveness.