Pith Number

pith:VAEMR37C

pith:2026:VAEMR37CTYWXWTUA3B2BG4LA4K

not attested not anchored not stored refs pending

Secure Cross-Silo Synthetic Genomic Data Generation

Daniil Filienko, Martine De Cock, Sikha Pentyala

Secure multiparty computation and differential privacy let multiple sites jointly train synthetic genomic data generators without exposing raw inputs.

arxiv:2604.27456 v2 · 2026-04-30 · cs.CR

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\usepackage{pith}
\pithnumber{VAEMR37CTYWXWTUA3B2BG4LA4K}

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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

Our approach combines secure multiparty computation (MPC) to ensure input privacy, so that no party ever discloses its data in unencrypted form, with differential privacy (DP) to provide output privacy by mitigating information leakage from the released synthetic data.

C2weakest assumption

That the utility of the synthetic data remains high enough for downstream AI tasks after applying both MPC and DP, even when data distributions differ across sites.

C3one line summary

A combination of MPC and DP enables federated training of synthetic genomic data generators across institutions while preserving input and output privacy.

Receipt and verification

First computed	2026-06-09T01:04:43.195999Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

a808c8efe29e2d7b4e80d874137160e2955dcf168b52420335fc29a5f086c5ff

Aliases

arxiv: 2604.27456 · arxiv_version: 2604.27456v2 · doi: 10.48550/arxiv.2604.27456 · pith_short_12: VAEMR37CTYWX · pith_short_16: VAEMR37CTYWXWTUA · pith_short_8: VAEMR37C

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/VAEMR37CTYWXWTUA3B2BG4LA4K \
  | 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: a808c8efe29e2d7b4e80d874137160e2955dcf168b52420335fc29a5f086c5ff

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "fd28f2f0b07c1bff8ec5a418772ee5fb93c6e65aab39e0361af95d65e1a08301",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CR",
    "submitted_at": "2026-04-30T05:52:49Z",
    "title_canon_sha256": "197796b4d71e8ac70b021351adb52f01e33d6788564b2c70a9d54ed8412b298e"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.27456",
    "kind": "arxiv",
    "version": 2
  }
}