Did you know that over 70 million of Dota2 players have their in-game data freely accessible? What if such data is used in malicious ways? This paper is the first to investigate such a problem. Motivated by the widespread popularity of video games, we propose the first threat model for Attribute Inference Attacks (AIA) in the Dota2 context. We explain how (and why) attackers can exploit the abundant public data in the Dota2 ecosystem to infer private information about its players. Due to lack of concrete evidence on the efficacy of our AIA, we empirically prove and assess their impact in reality. By conducting an extensive survey on $\sim$500 Dota2 players spanning over 26k matches, we verify whether a correlation exists between a player's Dota2 activity and their real-life. Then, after finding such a link ($p$ < 0.01 and $\rho$ > 0.3), we ethically perform diverse AIA. We leverage the capabilities of machine learning to infer real-life attributes of the respondents of our survey by using their publicly available in-game data. Our results show that, by applyingdomain expertise, some AIA can reach up to 98% precision and over 90% accuracy. This paper hence raises the alarm on a subtle, but concrete threat that can potentially affect the entire competitive gaming landscape. We alerted the developers of Dota2.

翻译：你知道吗？超过7000万Dota2玩家的游戏内数据可以免费获取。如果这些数据被恶意利用会怎样？本文首次对这一问题展开研究。受电子游戏广泛流行的启发，我们提出了Dota2环境下属性推断攻击（AIA）的首个威胁模型，阐释了攻击者如何（以及为何）利用Dota2生态系统中丰富的公开数据推断玩家的隐私信息。由于缺乏关于AIA效力的具体证据，我们通过实证方式验证并评估其现实影响。通过对涵盖26000余场比赛的约500名Dota2玩家进行大规模调查，我们首先验证了玩家Dota2活动与其现实生活之间的相关性。在发现显著关联（p<0.01且ρ>0.3）后，我们合乎道德地实施了多种AIA。利用机器学习能力，我们仅凭受访者公开的游戏数据即可推断其现实生活属性。结果表明，通过领域知识应用，部分AIA的精确率可达98%，准确率超过90%。本文因此对可能影响整个竞技游戏领域的潜在威胁敲响了警钟——我们已经向Dota2开发者发出预警。