Addressing Privacy and Security Concerns in Online Game Account Sharing: Detecting Players Using Mouse Dynamics

TY - CHAP

T1 - Addressing Privacy and Security Concerns in Online Game Account Sharing: Detecting Players Using Mouse Dynamics

AU - Wang, Yimiao

AU - Islam, Tasmina

N1 - Wang, Y. and Islam, T. (2023). Addressing Privacy and Security Concerns in Online Game Account Sharing: Detecting Players Using Mouse Dynamics. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM, ISBN 978-989-758-626-2; ISSN 2184-4313, pages 864-871. DOI: 10.5220/0011678300003411

PY - 2023/2/22

Y1 - 2023/2/22

N2 - As the internet has taken a huge part of people’s life, the personal information an online account can hold has increased as well, resulting in many concerns related to cybersecurity and privacy. Children as a vulnerable group could participate in risky actions unconsciously causing privacy leakage, like sharing a game account. This paper discusses the possible security and privacy risks caused by game account sharing and proposes a countermeasure based on user authentication to detect the true owner of the game account using their mouse dynamics. Support Vector Machine and Random Forest have been used for classification of the true owner and the intruder using players’ mouse dynamics data captured from “Minecraft” game. This paper also investigates the effect of different feature sets in detecting the players using feature ranking algorithms.

AB - As the internet has taken a huge part of people’s life, the personal information an online account can hold has increased as well, resulting in many concerns related to cybersecurity and privacy. Children as a vulnerable group could participate in risky actions unconsciously causing privacy leakage, like sharing a game account. This paper discusses the possible security and privacy risks caused by game account sharing and proposes a countermeasure based on user authentication to detect the true owner of the game account using their mouse dynamics. Support Vector Machine and Random Forest have been used for classification of the true owner and the intruder using players’ mouse dynamics data captured from “Minecraft” game. This paper also investigates the effect of different feature sets in detecting the players using feature ranking algorithms.

UR - http://www.scopus.com/inward/record.url?scp=85174483487&partnerID=8YFLogxK

U2 - 10.5220/0011678300003411

DO - 10.5220/0011678300003411

M3 - Conference paper

SN - 9789897586262

T3 - International Conference on Pattern Recognition Applications and Methods

SP - 864

EP - 871

BT - ICPRAM 2023 - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods, Volume 1

A2 - De Marsico, Maria

A2 - Sanniti di Baja, Gabriella

A2 - Fred, Ana L.N.

ER -