Multimodal game bot detection using user behavioral characteristics
Game industry, especially MMORPG (Massively Multiplayer Online Role Playing Game) has been rapidly expanding in these days. But at the same time, lots of online game security incidents have been increasing and getting more diverse. One of the most critical security incidents is 'Game Bots', which mimic human player's playing behaviors. Bot users can get a lot of benefic game elements (experience point, item, 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 bots from human players. Based on these features, we can construct a solution which can detect bots.
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