Using Group Interaction of Players to Prevent In-game Cheat in Network Games

Network games have become a popular social experience, while problem of in-game cheat (e.g. trade cheat, fraud and so on) has not an effective solution by now. It is reasonable to believe that cheaters and normal players have low group interactions with each other, and friends have high group interactions with each other. So, group interactions of players can help a given player to distinguish between righteous players who have high frequency of group interactions with famous virtuous roles or his dependable friends and suspectable players who have high frequency of group interactions with notorious roles. Some other suspectable players always like to be alone. In this paper, we develop an algorithm to visualize group interactions according to psychology of players and rules of the game system, and then we propose a simple method to prevent in-game cheat.