國立臺灣大學資訊工程學系Chen, Kuan-TaKuan-TaChenJiang, Jhih-WeiJhih-WeiJiangHuang, PollyPollyHuangChu, Hao-HuaHao-HuaChuLei, Chin-LaungChin-LaungLeiChen, Wen-ChinWen-ChinChen2006-09-272018-07-052006-09-272018-07-05200616876172http://ntur.lib.ntu.edu.tw//handle/246246/20060927122841632729https://www.scopus.com/inward/record.uri?eid=2-s2.0-59949083615&doi=10.1155%2f2009%2f797159&partnerID=40&md5=92a744ce3b01dd9477b2feb08bfe7ce3MMORPGs have become extremely popular among network gamers.Despite their success,one of MMORPG's great- est challenges is the increasing use of game bots,i.e.,auto- playing 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,of- ten patrol game zones and question suspicious players.This practice,however,is labor-intensive and ine ffective.To ad- dress this problem,we analyze the tra ffic generated by hu- man players vs.game bots and propose solutions to auto- matically identify game bots. Taking Ragnarok Online ,one of the most popular MMOGs, as our subject,we study the tra ffic generated by mainstream game bots and human players.We find that their tra ffic is distinguishable by:1)the regularity in the release time of client commands,2)the trend and magnitude of tra ffic burstiness in multiple time scales,and 3)the sensitivity to network conditions.We propose four strategies and two in- tegrated schemes to identify bots.For our data sets,the conservative scheme completely avoids making false accusa- tions 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.Massively multiplayer online role playing games (MMORPGs) have become extremely popular among network gamers. Despite their success, one of MMORPG's greatest challenges is the increasing use of game bots, that is, 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 versus game bots and propose general solutions to identify game bots. Taking Ragnarok Online as our subject, we study the traffic generated by human players and game bots. 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 different network conditions. Based on these findings, we propose four strategies and two ensemble schemes to identify bots. Finally, we discuss the robustness of the proposed methods against countermeasures of bot developers, and consider a number of possible ways to manage the increasingly serious bot problem.application/pdf931847 bytesapplication/pdfzh-TWGame BotOnline GamesTraffic BurstinessGeneral solutions; Human players; Massively multiplayer; Multiple time-scales; Network conditions; Release time; Role-playing games; Traffic analysis; Traffic burstiness; Game theoryjournal article2-s2.0-59949083615WOS:000260685800001http://ntur.lib.ntu.edu.tw/bitstream/246246/20060927122841632729/1/bot_ident.pdf