Multi-party Threshold Private Set Intersection with Sublinear Communication

Badrinarayanan, Saikrishna; Miao, Peihan; Raghuraman, Srinivasan; Rindal, Peter

doi:10.1007/978-3-030-75248-4_13

Cited by 22 publications

(28 citation statements)

References 36 publications

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“…Private intersection cardinality testing (PICT) refers to the problem of testing whether the intersection between sets of di erent parties is larger than a threshold T . Existing protocols that solve the PICT problem (e.g., [3,10,12]) are either only designed for the two-party case or for the multi-party case where each party inputs a private set and it is checked whether the size of the intersection of all these sets is larger than T . However, the privacy-preserving compatibility check for kidney exchange (cf.…”

Section: Private Intersection Cardinality Testingmentioning

confidence: 99%

“…And even if all such criteria are met, this is not a guarantee that a transplant can be executed between what was determined to be a compatible patient and donor. In fact, the nal decision as to whether a transplant should be carried out, lies with an experienced medical professional 3 . Consequently, our compatibility check gate is designed to include only such checks of criteria that in case they do not match between a donor and a patient render a transplant impossible.…”

Section: Relevant Medical Datamentioning

confidence: 99%

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A Privacy-Preserving Protocol for the Kidney Exchange Problem

Malte

Meyer

Wetzel

et al. 2020

Proceedings of the 19th Workshop on Privacy in the Electronic Society

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Kidney donations from living donors form an a ractive alternative to long waiting times on a list for a post-mortem donation. However, even if a living donor for a given patient is found, the donor's kidney might not meet the patient's medical requirements. If several patients are in this position, they may be able to exchange donors in a cyclic fashion. Current algorithmic approaches for determining such exchange cycles neglect the privacy requirements of donors and patients as they require their medical data to be centrally collected and evaluated. In this paper, we present the rst distributed privacy-preserving protocol for kidney exchange that ensures the correct computing of the exchange cycles while at the same time protecting the privacy of the patients' sensitive medical data. We prove correctness and security of the new protocol and evaluate its practical performance.

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Section: Private Intersection Cardinality Testingmentioning

confidence: 99%

Section: Relevant Medical Datamentioning

confidence: 99%

A Privacy-Preserving Protocol for the Kidney Exchange Problem

Malte

Meyer

Wetzel

et al. 2020

Proceedings of the 19th Workshop on Privacy in the Electronic Society

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“…The state-of-the-art protocol is due to Ghosh and Simkin [9], which builds on the idea of set reconciliation by Minsky et al [25] and uses oblivious polynomial evaluation as the underlying secure two-party cryptographic primitive. A similar construction by Badrinarayanan et al [2] replaces OPE with an additively homomorphic encryption scheme. Privacy-Preserving Proximity Detection: A loosely related task to DA-PSI is privacy-preserving proximity detection [27,42], wherein a trusted user of a service (say Alice) wants to learn if another user known to her (say Bob) is currently nearby.…”

Section: Related Workmentioning

confidence: 99%

“…The protocol does not have false negatives. Key Idea: The key observation behind the protocol is that F t-HQ ,d M ,d H can be realized as a two-step process: i) uniquely map the input vectors to sets, and ii) run a threshold PSI protocol [2,9] with these sets as inputs. For the first step, any deterministic mappings φ 1 , .…”

Section: Threshold Hamming Queriesmentioning

confidence: 99%

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Distance-Aware Private Set Intersection

Chakraborti¹,

Fanti²,

Reiter³

2021

Preprint

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Private set intersection (PSI) allows two mutually-untrusting parties to compute an intersection of their respective sets, without revealing any information to each other about items that are not in the intersection. This work introduces a variant of the problem called distance-aware PSI (DA-PSI) for computing intersection of items in defined metric spaces. The intersection contains pairs of items that are within a specified distance threshold of each other. This paper puts forward constructions for two such metric spaces: (i) Minkowski distance of order 1 over the set of integers (i.e., for integers a and b, their distance is |a − b|); and (ii) Hamming distance over the set {0, 1} . The communication volume scales logarithmically in the distance threshold, and linearly in the set size for the Minkowski DA-PSI protocol. On the other hand, the communication volume scales quadratically in the distance threshold for the Hamming DA-PSI protocol and is independent of the number of dimensions. Applying the Minkowski DA-PSI protocol to compare IP addresses contacting honeypots for private collaborative blacklisting both improves findings relative to PSI, doubling the number of IPs in the intersection, and reduces communication and computation by 10× relative to a naïve baseline. Applying the Hamming DA-PSI protocol to the task of Iris recognition reduces communication volume by 4× over a generic 2PC baseline.

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Multiparty Cardinality Testing for Threshold Private Intersection

Branco

Döttling

2021

Public-Key Cryptography – PKC 2021

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Multi-party Threshold Private Set Intersection with Sublinear Communication

Cited by 22 publications

References 36 publications

A Privacy-Preserving Protocol for the Kidney Exchange Problem

A Privacy-Preserving Protocol for the Kidney Exchange Problem

Distance-Aware Private Set Intersection

Multiparty Cardinality Testing for Threshold Private Intersection

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