Affiliation:
1. University at Buffalo, Buffalo
Abstract
Multiplayer online computer games are quickly growing in popularity, with millions of players logging in every day. While most play in accordance with the rules set up by the game designers, some choose to utilize artificially intelligent assistant programs, a.k.a. bots, to gain an unfair advantage over other players. In this article we demonstrate how an embedded noninteractive test can be used to prevent automatic artificially intelligent players from illegally participating in online game-play. Our solution has numerous advantages over traditional tests, such as its nonobtrusive nature, continuous verification, and simple noninteractive and outsourcing-proof design.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Science Applications
Cited by
13 articles.
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1. Detecting and Preventing Online Game Bots in MMORPGs;Encyclopedia of Computer Graphics and Games;2024
2. NGUARD+;ACM Transactions on Knowledge Discovery from Data;2020-10-06
3. NGUARD;Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining;2018-07-19
4. A time series classification approach to game bot detection;Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics;2017-06-19
5. Dissecting a Social Botnet;Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing;2015-02-28