MMORPGs have become extremely popular among network gamers. Despite their success, one of MMORPG's greatest challenges is the increasing use of game bots, i.e., autoplaying game clients. The use of game bots is considered unsportsmanlike and is therefore forbidden. To keep games in order, game police, played by actual human players, often patrol game zones and question suspicious players. This practice, however, is labor-intensive and ineffective. To address this problem, we analyze the traffic generated by human players vs. game bots and propose solutions to automatically identify game bots.

Taking Ragnarok Online, one of the most popular MMOGs, as our subject, we study the traffic generated by mainstream game bots and human players. We find that their traffic is distinguishable by: 1) the regularity in the release time of client commands, 2) the trend and magnitude of traffic burstiness in multiple time scales, and 3) the sensitivity to network conditions. We propose four strategies and two integrated schemes to identify bots. For our data sets, the conservative scheme completely avoids making false accusations against bona fide players, while the progressive scheme tracks game bots down more aggressively. Finally, we show that the proposed methods are generalizable to other games and robust against counter-measures from bot developers.

An extended version of this paper: Identifying MMORPG Bots: A Traffic Analysis Approach

Kuan-Ta Chen, Jhih-Wei Jiang, Polly Huang, Hao-Hua Chu, Chin-Laung Lei, and Wen-Chin Chen, "Identifying MMORPG Bots: A Traffic Analysis Approach," In Proceedings of ACM SIGCHI ACE 06, Los Angeles USA, Jun 2006.

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