Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 19, 08 December 2023
Open
Access | Article
Player identification based on player behavioral characteristics
* Author to whom correspondence should be addressed.
Abstract
In order to maintain a fair competition environment and enjoyable experience for players, millions of dollars have been spent on against cheating in video games. There is limited research on more sophisticated forms of cheating like “play-for-hire” whereby players pay others to play for themselves. Our work develops a model to identify each player from player behavioural characteristics, which will contribute to solve the “play-for-hire” problem. Firstly, we recorded interactions between players and the game as multivariate time series. Next, we tried to use CNN and LSTM to classify data as corresponding players and we do some feature processing and parameter optimization to improve our result. We found that LSTM is acting better than CNN in higher dimensions, which achieved an accuracy of nearly 87%.
Keywords
LSTM, CNN, multivariate, player’s behaviour.
References
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2. J. P. Pinto, A. Pimenta and P. Novais, "Deep Learning and Multivariate Time Series for Cheat Detection in Video Games," 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA), 2021, pp. 1-2, doi: 10.1109/DSAA53316.2021.9564219.
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Computing Innovation and Applied Physics
- ISBN (Print)
- 978-1-83558-203-9
- ISBN (Online)
- 978-1-83558-204-6
- Published Date
- 08 December 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/19/20230523
- Copyright
- 08 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited