Evidence map›Paper›PMID 41286986›Full record

ArticleGenome biology2025

A reinforcement learning-based approach for dynamic privacy protection in genomic data sharing beacons.

Masoud Poorghaffar Aghdam, Sobhan Shukueian Tabrizi, Kerem Ayöz, Erman Ayday, Sinem Sav, A Ercüment Çiçek

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Masoud Poorghaffar Aghdam *Bilkent University, Ankara, 06800, Türkiye.
Sobhan Shukueian Tabrizi *Bilkent University, Ankara, 06800, Türkiye.
Kerem AyözAmazon, Luxemburg, Luxemburg.
Erman AydayCase Western Reserve University, Cleveland, OH, 44106, USA.
Sinem SavBilkent University, Ankara, 06800, Türkiye. sinem.sav@cs.bilkent.edu.tr.
A Ercüment ÇiçekBilkent University, Ankara, 06800, Türkiye. cicek@cs.bilkent.edu.tr.

Funding

National Library of Medicine of the National Institutes of Health R01LM013429
6 · The paper itself

Abstract

The rise of genomic sequencing raises privacy concerns due to the identifiable nature of genomic data. The GA4GH Beacon Project enables privacy-preserving data sharing but is vulnerable to membership inference attacks that reveal individual participation. Existing defenses, such as noise addition and query restrictions, rely on static policies that attackers can bypass. We introduce the first reinforcement learning (RL)-based dynamic defense for the beacon protocol, training defender and attacker agents in a multiplayer setting. Our approach adapts responses in real time, distinguishing users from adversaries and balancing privacy with utility against evolving threats.

Indexed as

Genetic PrivacyGenomicsInformation DisseminationHumansReinforcement Machine LearningGame theoryGenome privacyGenomic data-sharing beaconsReinforcement learning

Identifiers

PMID41286986
PMCPMC12642032

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.