BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data
Continuous authentication in high-stakes digital environments requires datasets with fine-grained behavioral signals under realistic cognitive and motor demands. But current benchmarks are often limited by small scale, unimodal sensing or lack of synchronised environmental context. To address this gap, this paper introduces BEACON (Behavioral Engine for Authentication & Continuous Monitoring), a large-scale multimodal dataset that captures diverse skill tiers in competitive Valorant gameplay. BEACON contains approximately 430 GB of synchronised modality data (461 GB total on-disk including auxiliary Valorant configuration captures) from 79 sessions across 28 distinct players, estimated at...
| Authors | Ishpuneet Singh, Gursmeep Kaur, Uday Pratap Singh Atwal et al. |
|---|---|
| Primary category | cs.CR |
| Published | 11 May 2026 |
| Last updated at source | 15 May 2026 |
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- beacon-gui/BEACON-DatasetDataset · cited by
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- beacon-gui/BEACON-DatasetDataset
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