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

fYear

2015

fDate

24-27 March 2015

Firstpage

406

Lastpage

413

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Information Networking and Applications (AINA), 2015 IEEE 29th International Conference on

Conference_Location

Gwangiu

ISSN

1550-445X

Print_ISBN

978-1-4799-7904-2

Type

conf

DOI

10.1109/AINA.2015.214

Filename

7097999