New usage of telemetry for anti-cheating in FPS game

Zilu Wang
{"title":"New usage of telemetry for anti-cheating in FPS game","authors":"Zilu Wang","doi":"10.54254/2753-8818/30/20241075","DOIUrl":null,"url":null,"abstract":"First-person shooter games are experiencing a surge in popularity. As more players join, advanced AI-based cheats have emerged. These cheats simulate human gameplay, sending mouse inputs, making them hard to detect and counter. Therefore, this research presents a novel approach that utilizes telemetry data analysis to identify and counteract cheating in FPS games. The main objective of this study is to develop an innovative anti-cheating system that can effectively detect and prevent players from exploiting AI-based cheats to gain unfair advantages. To achieve this, extensive telemetry data is collected during gameplay. The data contains the real-time cursor position when the player is playing the game. Besides, Machine learning and deep algorithms are applied to analyse the telemetry data and distinguish between human player behaviour and AI-driven cheating patterns. Decision Tree, Random Forest, LSTM, and CNN are applied for this research. And in the final evaluation, CNNs accuracy reached around 80% which proves it is a possible mode to be used for this problem. The significance of this research lies in its contribution against cheating in FPS games, particularly those exploiting AI technologies to gain unfair advantage. The proposed telemetry-based approach offers a solution to safeguard competitive gaming and insight into the game company based on this novel way for further experiments.","PeriodicalId":489336,"journal":{"name":"Theoretical and Natural Science","volume":" 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theoretical and Natural Science","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.54254/2753-8818/30/20241075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

First-person shooter games are experiencing a surge in popularity. As more players join, advanced AI-based cheats have emerged. These cheats simulate human gameplay, sending mouse inputs, making them hard to detect and counter. Therefore, this research presents a novel approach that utilizes telemetry data analysis to identify and counteract cheating in FPS games. The main objective of this study is to develop an innovative anti-cheating system that can effectively detect and prevent players from exploiting AI-based cheats to gain unfair advantages. To achieve this, extensive telemetry data is collected during gameplay. The data contains the real-time cursor position when the player is playing the game. Besides, Machine learning and deep algorithms are applied to analyse the telemetry data and distinguish between human player behaviour and AI-driven cheating patterns. Decision Tree, Random Forest, LSTM, and CNN are applied for this research. And in the final evaluation, CNNs accuracy reached around 80% which proves it is a possible mode to be used for this problem. The significance of this research lies in its contribution against cheating in FPS games, particularly those exploiting AI technologies to gain unfair advantage. The proposed telemetry-based approach offers a solution to safeguard competitive gaming and insight into the game company based on this novel way for further experiments.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
在 FPS 游戏中使用遥测技术反作弊的新方法
第一人称射击游戏的受欢迎程度正在激增。随着越来越多的玩家加入,出现了先进的人工智能作弊器。这些作弊器模拟人类游戏,发送鼠标输入,使其难以检测和反制。因此,本研究提出了一种新方法,利用遥测数据分析来识别和反击 FPS 游戏中的作弊行为。本研究的主要目的是开发一种创新的反作弊系统,该系统可有效检测并防止玩家利用基于人工智能的作弊技术获得不公平的优势。为此,我们在游戏过程中收集了大量遥测数据。这些数据包含玩家玩游戏时光标的实时位置。此外,还应用了机器学习和深度算法来分析遥测数据,并区分人类玩家行为和人工智能驱动的作弊模式。本研究采用了决策树、随机森林、LSTM 和 CNN。在最终评估中,CNN 的准确率达到了 80%左右,这证明它是一种可以用于这一问题的模式。这项研究的意义在于,它有助于打击 FPS 游戏中的作弊行为,特别是那些利用人工智能技术获取不公平优势的行为。所提出的基于遥测的方法为保护竞技游戏提供了一种解决方案,并基于这种新方法对游戏公司进行了深入了解,以供进一步实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Road dynamic landscape design and simulation based on fuzzy clustering algorithm Quantum physics: A better model to understand consciousness-related brain functions Automatic pricing and replenishment decision-making for vegetable products based on optimization models Parking recommendation with meta-heuristic algorithms Order-six complex hadamard matrices constructed by Schmidt rank and partial transpose in operator algebra
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1