| 電子情報通信学会 研究会発表申込システム 講演論文 詳細 |
技報閲覧サービス [ログイン] 技報アーカイブ |
| トップに戻る | 前のページに戻る | [Japanese] / [English] |
| 講演抄録／キーワード | ||
| 講演名 | 2024-11-01 09:20 Consistent Team, Consistent Data: Authenticating Esports Players Through In-Game Behavioral Data and Game-State Analysis with Uniform Team Composition ○Franziska Zimmer・Mhd Irvan・Roberta Tamponi・Maharage Nisansala Sevwandi Perera・Ryosuke Kobayashi・Rie Shigetomi Yamaguchi（The University of Tokyo）  BioX2024-83 |
|
| 抄録 | （和） | In esports, teamwork is crucial for winning, with each player performing specific roles. However, can a player be uniquely authenticated within their team? The potential of using game-state and in-game behavioral data for biometric authentication is not fully understood. This study focuses on the unique authentication of players within the same team using data from a specific map in Counter-Strike: Global Offensive. Our findings demonstrate that team members can be uniquely authenticated with up to 96.92% accuracy. |
| （英） | In esports, teamwork is crucial for winning, with each player performing specific roles. However, can a player be uniquely authenticated within their team? The potential of using game-state and in-game behavioral data for biometric authentication is not fully understood. This study focuses on the unique authentication of players within the same team using data from a specific map in Counter-Strike: Global Offensive. Our findings demonstrate that team members can be uniquely authenticated with up to 96.92% accuracy. | |
| キーワード | （和） | Authentication / Machine learning / User behavior / Esports / Gaming / / / |
| （英） | Authentication / Machine learning / User behavior / Esports / Gaming / / / | |
| 文献情報 | 信学技報, vol. 124, no. 226, BioX2024-83, pp. 65-70, 2024年10月. | |
| 資料番号 | BioX2024-83 | |
| 発行日 | 2024-10-24 (BioX) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| 著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します．(許諾番号：10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| PDFダウンロード | BioX2024-83 |
|
[研究会発表申込システムのトップページに戻る]