TY - GEN
T1 - Detection of auto programs for MMORPGs
AU - Kim, Hyungil
AU - Hong, Sungwoo
AU - Kim, Juntae
PY - 2005
Y1 - 2005
N2 - Auto-playing programs are often used on behalf of human players in a MMORPG(Massively Multi-player Online Role Playing Game). By playing automatically and continuously, it helps to speed up the game character's level-up process. However, the auto-playing programs, either software or hardware, do harm to games servers in various ways including abuse of resources. In this paper, we propose a way of detecting the auto programs by analyzing the window event sequences produced by the game players. In our proposed method, the event sequences are transformed into a set of attributes, and various learning algorithms are applied to classify the data represented by the set of attribute values into human or auto player. The results from experiments with several MMORPGs show that the Decision Tree learning with proposed method can identify the auto-playing programs with high accuracy.
AB - Auto-playing programs are often used on behalf of human players in a MMORPG(Massively Multi-player Online Role Playing Game). By playing automatically and continuously, it helps to speed up the game character's level-up process. However, the auto-playing programs, either software or hardware, do harm to games servers in various ways including abuse of resources. In this paper, we propose a way of detecting the auto programs by analyzing the window event sequences produced by the game players. In our proposed method, the event sequences are transformed into a set of attributes, and various learning algorithms are applied to classify the data represented by the set of attribute values into human or auto player. The results from experiments with several MMORPGs show that the Decision Tree learning with proposed method can identify the auto-playing programs with high accuracy.
KW - Data Mining
KW - Entertainment and AI
KW - Intelligent Data Analysis
KW - Machine Learning
UR - http://www.scopus.com/inward/record.url?scp=33745635378&partnerID=8YFLogxK
U2 - 10.1007/11589990_187
DO - 10.1007/11589990_187
M3 - Conference contribution
AN - SCOPUS:33745635378
SN - 3540304622
SN - 9783540304623
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1281
EP - 1284
BT - AI 2005
PB - Springer Verlag
T2 - 18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence
Y2 - 5 December 2005 through 9 December 2005
ER -