arXiv:2608.24893v2 Announce Type: replace
Abstract: In competitive first-person shooter (FPS) games such as Counter-Strike 2 (CS2), account-integrity review often asks whether an account's recent behavior remains consistent with its historical operator. This consistency question arises in cases such as temporary substitution, rank boosting, and high-skill players using lower-ranked accounts, where manual review requires comparing a current match against multiple historical matches. We formulate this review task as same-player verification: we encode the behavioral trajectory of a single player in a match replay (demo) as a demo-player behavioral fingerprint, and train a model to judge whether two behavioral observations come from the same real player. Using CS2-specific domain knowledge, the fingerprints cover crosshair control, movement-stop-fire coordination, economy/buy, combat/engagement, and temporal rhythm. We construct strict six-fold evaluations on the Perfect dataset (3,570 demos and 35,700 demo-player observations) and the Professional dataset (539 demos and 5,390 demo-player observations). The final pairwise model reaches ROC AUCs of 0.926 and 0.956, respectively. Feature analysis shows that the strongest identity signals come from aiming/crosshair and other low-level mechanical behaviors, indicating that stable mechanics are more informative for this verification task than single-match performance outcomes. On fixed eligible query cohorts, aggregating pairwise evidence between a current demo and multiple historical demos raises account-history AUC on Perfect from 0.923 at K=1 to 0.982 at K=10, and on Professional from 0.914 at K=1 to 0.975 at K=5. These results show that CS2 demo behavior can support supervised same-player verification and account-level identity-consistency modeling through multi-demo history aggregation.
Abstract: In competitive first-person shooter (FPS) games such as Counter-Strike 2 (CS2), account-integrity review often asks whether an account's recent behavior remains consistent with its historical operator. This consistency question arises in cases such as temporary substitution, rank boosting, and high-skill players using lower-ranked accounts, where manual review requires comparing a current match against multiple historical matches. We formulate this review task as same-player verification: we encode the behavioral trajectory of a single player in a match replay (demo) as a demo-player behavioral fingerprint, and train a model to judge whether two behavioral observations come from the same real player. Using CS2-specific domain knowledge, the fingerprints cover crosshair control, movement-stop-fire coordination, economy/buy, combat/engagement, and temporal rhythm. We construct strict six-fold evaluations on the Perfect dataset (3,570 demos and 35,700 demo-player observations) and the Professional dataset (539 demos and 5,390 demo-player observations). The final pairwise model reaches ROC AUCs of 0.926 and 0.956, respectively. Feature analysis shows that the strongest identity signals come from aiming/crosshair and other low-level mechanical behaviors, indicating that stable mechanics are more informative for this verification task than single-match performance outcomes. On fixed eligible query cohorts, aggregating pairwise evidence between a current demo and multiple historical demos raises account-history AUC on Perfect from 0.923 at K=1 to 0.982 at K=10, and on Professional from 0.914 at K=1 to 0.975 at K=5. These results show that CS2 demo behavior can support supervised same-player verification and account-level identity-consistency modeling through multi-demo history aggregation.
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