Evidence map›Paper›PMID 36138474›Full record

ArticleBMC medical informatics and decision making2022

SPIKE: secure and private investigation of the kidney exchange problem.

Timm Birka, Kay Hamacher, Tobias Kussel, Helen Möllering, Thomas Schneider

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2022. 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

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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

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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

5 authors.

Timm Birka *ENCRYPTO, Technical University of Darmstadt, Darmstadt, Germany.
Kay HamacherComputational Biology and Simulation group, Technical University of Darmstadt, Darmstadt, Germany.
Tobias KusselComputational Biology and Simulation group, Technical University of Darmstadt, Darmstadt, Germany.
Helen MölleringENCRYPTO, Technical University of Darmstadt, Darmstadt, Germany. moellering@encrypto.cs.tu-darmstadt.de.
Thomas SchneiderENCRYPTO, Technical University of Darmstadt, Darmstadt, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe kidney exchange problem (KEP) addresses the matching of patients in need for a replacement organ with compatible living donors. Ideally many medical institutions should participate in a matching program to increase the chance for successful matches. However, to fulfill legal requirements current systems use complicated policy-based data protection mechanisms that effectively exclude smaller medical facilities to participate. Employing secure multi-party computation (MPC) techniques provides a technical way to satisfy data protection requirements for highly sensitive personal health information while simultaneously reducing the regulatory burdens.

resultsWe have designed, implemented, and benchmarked SPIKE, a secure MPC-based privacy-preserving KEP protocol which computes a locally optimal solution by finding matching donor-recipient pairs in a graph structure. SPIKE matches 40 pairs in cycles of length 2 in less than 4 min and outperforms the previous state-of-the-art protocol by a factor of [Formula: see text] in runtime while providing medically more robust solutions.

conclusionsWe show how to solve the KEP in a robust and privacy-preserving manner achieving significantly more practical performance than the current state-of-the-art (Breuer et al., WPES'20 and CODASPY'22). The usage of MPC techniques fulfills many data protection requirements on a technical level, allowing smaller health care providers to directly participate in a kidney exchange with reduced legal processes. As sensitive data are not leaving the institutions' network boundaries, the patient data underlie a higher level of protection than in the currently employed (centralized) systems. Furthermore, due to reduced legal barriers, the proposed decentralized system might be simpler to implement in a transnational, intereuropean setting with mixed (national) data protecion laws.

Indexed as

Computer SecurityPrivacyHumansKidneyKidney-exchangePrivacySecure multi-party computation (MPC)

Identifiers

PMID36138474
PMCPMC9502669

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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 OpenQuestion graph.