Pith Number

pith:PRNR4GCY

pith:2026:PRNR4GCYEP7QP3REOBUKOV3LZM

not attested not anchored not stored refs resolved

BEACON: A Multimodal Dataset for Learning Behavioral Fingerprints from Gameplay Data

Guramrit Singh, Gurjot Singh, Gursmeep Kaur, Ishpuneet Singh, Maninder Singh, Uday Pratap Singh Atwal

A new multimodal dataset from competitive gameplay provides synchronized behavioral signals for testing continuous authentication systems.

arxiv:2605.10867 v2 · 2026-05-11 · cs.CR · cs.AI · cs.CV · cs.LG · cs.NI

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\pithnumber{PRNR4GCYEP7QP3REOBUKOV3LZM}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

BEACON contains approximately 430 GB of synchronised modality data from 79 sessions across 28 distinct players, estimated at 102.51 hours of active gameplay, including high-frequency mouse dynamics, keystroke events, network packet captures, screen recordings, hardware metadata, and in-game configuration context.

C2weakest assumption

The high precision motor skills and high cognitive load inherent to tactical shooters make the collected data a rigorous stress test for the robustness of behavioral biometrics.

C3one line summary

BEACON is a large-scale multimodal dataset of synchronized Valorant esports gameplay data for behavioral fingerprinting and continuous authentication research.

References

39 extracted · 39 resolved · 1 Pith anchors

[1] Integrating big data analytics and behavioral biometrics for advanced fraud detection.Sakarya University Journal of Computer and Information Sciences, 9(1):8–20 2026 · doi:10.35377/saucis

[2] Sapimouse: Mouse dynamics-based user authentication using deep feature learning 2021 · doi:10.1109/saci51354.2021.9465583

[3] Realistic website fingerprinting by augmenting network traces 2023 · doi:10.1145/3576915.3616639

[4] Var-cnn and dynaflow: Improved attacks and defenses for website fingerprinting.CoRR, abs/1802.10215 2018 · arXiv:1802.10215

[5] Sc2egset: Starcraft ii esport replay and game-state dataset.Scientific Data, 10(1):600, Sep 2023 2023 · doi:10.1038/s41597-023-02510-7

Receipt and verification

First computed	2026-05-20T00:01:43.797666Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

7c5b1e185823ff07ee247068a7576bcb193fb52b9a9878b618e78494979f5df1

Aliases

arxiv: 2605.10867 · arxiv_version: 2605.10867v2 · doi: 10.48550/arxiv.2605.10867 · pith_short_12: PRNR4GCYEP7Q · pith_short_16: PRNR4GCYEP7QP3RE · pith_short_8: PRNR4GCY

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/PRNR4GCYEP7QP3REOBUKOV3LZM \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 7c5b1e185823ff07ee247068a7576bcb193fb52b9a9878b618e78494979f5df1

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e95139f76dbb57cbb7893e0fbc96be8d087ee571519213f824e5bd2138483c59",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.CV",
      "cs.LG",
      "cs.NI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CR",
    "submitted_at": "2026-05-11T17:17:02Z",
    "title_canon_sha256": "ec8bd3d776da47760665b4b21effa83e1cadcaf1e15be72ccd8fd6fc2bce91c7"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.10867",
    "kind": "arxiv",
    "version": 2
  }
}