{"title":"我知道bot昨天做了什么:使用Naïve贝叶斯算法进行全动作序列分析","authors":"Jina Lee, Jiyoun Lim, Wonjun Cho, H. Kim","doi":"10.1109/NETGAMES.2013.6820611","DOIUrl":null,"url":null,"abstract":"A game BOT is a major threat in the online game industry. There have been many efforts to distinguish game BOT users from normal users. Several studies have proposed BOT detection models based on the analysis of users' in-game action sequence data. These studies indicated that the analysis of users' in-game actions is effective to detect BOTs. However, they do not use sufficiently large data sets to train and test their algorithms. In this paper, we have proposed a BOT detection model that uses users' in-game action sequence data obtained with the aid of big data analysis environments. We did empirical analysis of the dataset of “Blade and Soul”, the third largest MMORPG in Korea. The result shows that a large amount of sequence data leads to high accuracy.","PeriodicalId":289229,"journal":{"name":"2013 12th Annual Workshop on Network and Systems Support for Games (NetGames)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"I know what the BOTs did yesterday: Full action sequence analysis using Naïve Bayesian algorithm\",\"authors\":\"Jina Lee, Jiyoun Lim, Wonjun Cho, H. Kim\",\"doi\":\"10.1109/NETGAMES.2013.6820611\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A game BOT is a major threat in the online game industry. There have been many efforts to distinguish game BOT users from normal users. Several studies have proposed BOT detection models based on the analysis of users' in-game action sequence data. These studies indicated that the analysis of users' in-game actions is effective to detect BOTs. However, they do not use sufficiently large data sets to train and test their algorithms. In this paper, we have proposed a BOT detection model that uses users' in-game action sequence data obtained with the aid of big data analysis environments. We did empirical analysis of the dataset of “Blade and Soul”, the third largest MMORPG in Korea. The result shows that a large amount of sequence data leads to high accuracy.\",\"PeriodicalId\":289229,\"journal\":{\"name\":\"2013 12th Annual Workshop on Network and Systems Support for Games (NetGames)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 12th Annual Workshop on Network and Systems Support for Games (NetGames)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NETGAMES.2013.6820611\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 12th Annual Workshop on Network and Systems Support for Games (NetGames)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NETGAMES.2013.6820611","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
摘要
游戏BOT是网络游戏行业的一大威胁。为了区分游戏BOT用户和普通用户,人们做了很多努力。一些研究提出了基于用户在游戏中的动作序列数据分析的BOT检测模型。这些研究表明,分析用户在游戏中的行为是检测bot的有效方法。然而,他们没有使用足够大的数据集来训练和测试他们的算法。在本文中,我们提出了一种BOT检测模型,该模型利用大数据分析环境下获得的用户在游戏中的动作序列数据。我们对韩国第三大MMORPG《Blade and Soul》的数据集进行了实证分析。结果表明,大量的序列数据可以提高识别精度。
I know what the BOTs did yesterday: Full action sequence analysis using Naïve Bayesian algorithm
A game BOT is a major threat in the online game industry. There have been many efforts to distinguish game BOT users from normal users. Several studies have proposed BOT detection models based on the analysis of users' in-game action sequence data. These studies indicated that the analysis of users' in-game actions is effective to detect BOTs. However, they do not use sufficiently large data sets to train and test their algorithms. In this paper, we have proposed a BOT detection model that uses users' in-game action sequence data obtained with the aid of big data analysis environments. We did empirical analysis of the dataset of “Blade and Soul”, the third largest MMORPG in Korea. The result shows that a large amount of sequence data leads to high accuracy.