# Who Is Alyx? A new Behavioral Biometric Dataset for User Identification in XR

arXiv: https://arxiv.org/abs/2308.03788 · HTML: https://mlsanity.com/paper/2308.03788/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Aug 2023.

## Built on by (most cited first, 7 of 7)

- [Motion-Based User Identification across XR and Metaverse Applications by Deep Classification and Similarity Learning](https://mlsanity.com/paper/2509.08539/) (2025)
- [Using Motion Forecasting for Behavior-Based Virtual Reality (VR) Authentication](https://mlsanity.com/paper/2401.16649/) (2024)
- [The Full-scale Assembly Simulation Testbed (FAST) Dataset](https://mlsanity.com/paper/2403.08969/) (2024)
- [Predicting 3D Motion from 2D Video for Behavior-Based VR Biometrics](https://mlsanity.com/paper/2502.04361/) (2025)
- [Unobtrusive In-Situ Measurement of Behavior Change by Deep Metric Similarity Learning of Motion Patterns](https://mlsanity.com/paper/2509.04174/) (2025)
- [Deep Learning for Virtual Reality User Identification: A Benchmark](https://mlsanity.com/paper/2604.16341/) (2026)
- [BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data](https://mlsanity.com/paper/2605.10867/) (2026)

## Abstract (arXiv)

This article presents a new dataset containing motion and physiological data of users playing the game "Half-Life: Alyx". The dataset specifically targets behavioral and biometric identification of XR users. It includes motion and eye-tracking data captured by a HTC Vive Pro of 71 users playing the game on two separate days for 45 minutes. Additionally, we collected physiological data from 31 of these users. We provide benchmark performances for the task of motion-based identification of XR users with two prominent state-of-the-art deep learning architectures (GRU and CNN). After training on the first session of each user, the best model can identify the 71 users in the second session with a mean accuracy of 95% within 2 minutes. The dataset is freely available under https://github.com/cschell/who-is-alyx