Bot Detection Models and Corresponding Game Security Processes in Computer Online Games

• Main Authors: Shiou-hung Chen, 陳首宏
• Other Authors: Nai-wei Lo
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/g98727

碩士 === 國立臺灣科技大學 === 資訊管理系 === 94 === Computer online games are popular and have good prospects of investment profit to on-line game producers in recent years. Since playing on-line games are very competitive and time-consuming, many players try to use illegal software agent (we call it BOT) to play for them. Thus, BOTs can automatically train players’ game roles and get advanced ranks for their game roles. The goal of our research is to detect the Bots used in games and provide a standard management process to handle BOT-detected situation. The research constructs a complete process which includes historical data mining/analysis, BOT identification, BOT confirmation and player punishment mechanism. In historical data mining/analysis, we use the decision tree method to make our BOT-detection rule that could filter out possible BOT players. In BOT identification stage, we implement CAPTCHA mechanism to inspect whether an online game player is a BOT or not. In BOT confirmation stage, field-side game manager will trace and check the potential Bot player who is identified during the BOT identification stage to prevent false-positive situation. Once a BOT players are confirmed, player punishment mechanism will be activated.