Title :
Detection of Illegal Players in Massively Multiplayer Online Role Playing Game by Classification Algorithms
Author :
Zhongqqiang Zhang ; Anada, Hiroaki ; Kawamoto, Junpei ; Sakurai, Kouichi
Author_Institution :
Grad. Sch. of Inf. Sci. & Electr. Eng., Kyushu Univ., Fukuoka, Japan
Abstract :
Online games have become one of the most popular games in recent years. However, fraud such as real money trading and the use of game bot, has also increased accordingly. In order to maintain a balance in the virtual world, the operators of online games have taken a stern response to the players who conduct fraud. In this study, we have sorted out players´ behaviors based on players´ game playing time in order to support and find potentially illegal players in the MMORPG. In this paper, we added a topic model to the experiment and used k-means as a major tool to classify the players in the World of War craft Avatar History Dataset and find potentially illegal players.
Keywords :
behavioural sciences; computer games; fraud; pattern classification; MMORPG; World of Warcraft Avatar History Dataset; classification algorithms; fraud; illegal player detection; k-means; massively multiplayer online role playing game; online games; player behaviors; player game playing time; virtual world; Algorithm design and analysis; Avatars; Classification algorithms; Clustering algorithms; Euclidean distance; Games; Resource management; Online game; classify; fraud; k-means; topic model;
Conference_Titel :
Advanced Information Networking and Applications (AINA), 2015 IEEE 29th International Conference on
Conference_Location :
Gwangiu
Print_ISBN :
978-1-4799-7904-2
DOI :
10.1109/AINA.2015.214
