VESPA: A General System for Vision-Based Extrasensory Perception Anticheating in Online FPS Games

被引:0
|
作者
Zhao, Shiwei [1 ]
Qi, Jiaheng [1 ]
Hu, Zhipeng [1 ]
Yan, Han [1 ]
Wu, Runze [1 ]
Shen, Xudong [1 ]
Lv, Tangjie [1 ]
Fan, Changjie [1 ]
机构
[1] NetEase Games, Fuxi AI Lab, Hangzhou 310052, Peoples R China
关键词
Games; Visualization; Servers; Image reconstruction; Training; Data privacy; Companies; Anticheating system; extrasensory perception (ESP); industrial applications; online first-person shooter (FPS) games;
D O I
10.1109/TG.2023.3327115
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Cheating is widespread in online games, particularly in competitive games, such as first-person shooter (FPS) games. One of the most common types of cheating is extrasensory perception (ESP), which involves illicitly obtaining visual information to gain an unfair advantage over normal players. To protect the gaming experience of legitimate players and the interests of game companies, there is an urgent need for anticheating applications. In this article, we propose a general system for ESP anticheating in online FPS games, considering the business characteristics and industrial applications. We present a vision-based anticheating framework that incorporates both supervised and unsupervised solutions for comprehensive cheating detection. Based on this framework, we design and deploy a dual-audit human-in-the-loop system for industrial gaming anticheating applications. We evaluate our proposed framework from multiple online and offline perspectives and demonstrate its practical significance with superior performance.
引用
收藏
页码:611 / 620
页数:10
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