Paper Citation Record · LEDGER

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2506.01072.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.01072 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:01:42.481444Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

verified exact0
verified fuzzy32
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 74d90426-781e-4599-9022-597929a34661 · outbound

This paper cites When homomorphic encryption marries secret sharing: Secure large-scale sparse logistic regression and applications in risk control,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning When homomorphic encryption marries secret sharing: Secure large-scale sparse logistic regression and applications in risk control,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.893553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5b0fb57d-a35e-4dc5-b850-85ecaf9349f7 · outbound

This paper cites Ents: An efficient three-party training framework for decision trees by communication optimization,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Ents: An efficient three-party training framework for decision trees by communication optimization,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.880417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9ab3a12c-4ac2-4c02-b4eb-f6c674fb3216 · outbound

This paper cites Secureml: A system for scalable privacy- preserving machine learning,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Secureml: A system for scalable privacy- preserving machine learning,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.868385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9f52cc1a-7771-4995-9b15-0cb491f5d01f · outbound

This paper cites Practi- cal multi-party private set intersection from symmetric-key techniques,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Practi- cal multi-party private set intersection from symmetric-key techniques,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.854263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8fb65c99-6e3f-4803-ba2a-7a33dbdbaa1b · outbound

This paper cites Scalable private set intersection based on ot extension,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Scalable private set intersection based on ot extension,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.843022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4a7fe91b-91b4-4a89-9c6d-04ec342edcb3 · outbound

This paper cites Multi-party private set intersection protocols for practical applications.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Multi-party private set intersection protocols for practical applications

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.831230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 64d33a06-9402-421c-a098-d8e3e7897843 · outbound

This paper cites O-Ring and K-Star: Efficient multi- party private set intersection,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning O-Ring and K-Star: Efficient multi- party private set intersection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.819998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1139d608-0a06-499f-b8ee-db8465472508 · outbound

This paper cites Comprehensive analysis of privacy leakage in vertical federated learning during prediction.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Comprehensive analysis of privacy leakage in vertical federated learning during prediction

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.807491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 46a2ced7-a7e1-4248-9d92-73c686d631ff · outbound

This paper cites Peafowl: Private entity alignment in multi-party privacy-preserving machine learning,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Peafowl: Private entity alignment in multi-party privacy-preserving machine learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.795841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ed1c96cb-39a5-4d09-a832-32fa6759bc71 · outbound

This paper cites iprivjoin: An id-private data join framework for privacy-preserving machine learning,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning iprivjoin: An id-private data join framework for privacy-preserving machine learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.784370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ff933fa5-4b03-4643-965b-5b2ed5d16a2b · outbound

This paper cites Circuit-psi with linear complexity via relaxed batch opprf,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Circuit-psi with linear complexity via relaxed batch opprf,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.773937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 467f0702-05f8-4859-ba3a-d4f840a1ff95 · outbound

This paper cites MP-SPDZ: A versatile framework for multi-party computa- tion,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning MP-SPDZ: A versatile framework for multi-party computa- tion,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.763888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bb7064ba-ecce-4bbc-85b2-2dbeda7ac955 · outbound

This paper cites Efficient scalable multiparty private set-intersection via garbled bloom filters,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Efficient scalable multiparty private set-intersection via garbled bloom filters,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.753577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b219a041-b92b-48b0-afcf-e0adc0c3038e · outbound

This paper cites Efficient scalable multi-party private set intersection using oblivious prf,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Efficient scalable multi-party private set intersection using oblivious prf,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.741392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 74562015-1664-47dd-86e3-ec9bc14b8564 · outbound

This paper cites Practical multi-party private set intersection protocols,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Practical multi-party private set intersection protocols,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.731212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b3a9340e-6df1-4d82-b9fd-76a1e48f7be8 · outbound

This paper cites O-ring and k-star: Efficient multi- party private set intersection,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning O-ring and k-star: Efficient multi- party private set intersection,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.720843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 72a3174b-6530-40b0-af74-cfe849d34f1b · outbound

This paper cites Private set intersection: Are garbled circuits better than custom protocols?.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Private set intersection: Are garbled circuits better than custom protocols?

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.710074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 26cc2589-c897-4591-b9b1-c14f67e957ca · outbound

This paper cites V ole-psi: fast oprf and circuit-psi from vector-ole,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning V ole-psi: fast oprf and circuit-psi from vector-ole,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.699275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4ae7f78a-8125-4d56-a496-4e8fd30dc00b · outbound

This paper cites Obliv- ious key-value stores and amplification for private set intersection,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Obliv- ious key-value stores and amplification for private set intersection,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.686925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1cdc0ac0-2039-4285-ab2c-886306e0b436 · outbound

This paper cites Blazing fast psi from improved okvs and subfield vole.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Blazing fast psi from improved okvs and subfield vole

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.674590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 63afbd84-5a6c-4685-83cf-7b87f7e71946 · outbound

This paper cites Secure-computation-friendly private set intersection from oblivious compact graph evaluation,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Secure-computation-friendly private set intersection from oblivious compact graph evaluation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.663638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 52230ab8-f8ce-4104-9871-1d66c03c170a · outbound

This paper cites Prism: Private verifiable set computation over multi-owner outsourced databases,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Prism: Private verifiable set computation over multi-owner outsourced databases,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.651438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bb2f9efb-3fe7-44a1-980e-4962888b6a9c · outbound

This paper cites Efficient linear multiparty psi and extensions to circuit/quorum psi,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Efficient linear multiparty psi and extensions to circuit/quorum psi,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.640616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 500e18c3-5057-41c8-b3d1-c7186a81c47a · outbound

This paper cites Universally composable security: A new paradigm for cryptographic protocols,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Universally composable security: A new paradigm for cryptographic protocols,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.628511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b87109a2-c620-4ed5-900a-630c8258203a · outbound

This paper cites Cuckoo hashing,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Cuckoo hashing,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.615517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dfd302f2-500e-446f-aaa3-dae626c89d10 · outbound

This paper cites Keyword search and oblivious pseudorandom functions,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Keyword search and oblivious pseudorandom functions,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.603721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a144eb42-9dbc-4831-aade-5b7737117673 · outbound

This paper cites Aby-a framework for efficient mixed-protocol secure two-party computation.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Aby-a framework for efficient mixed-protocol secure two-party computation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T12:01:42.456320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c3efbf8-86d7-4ecc-9734-ff90539d9237 · outbound

This paper cites Pir-psi: scaling private contact discovery,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Pir-psi: scaling private contact discovery,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.581851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e67478ee-7376-47b1-82f9-fc0494d64f69 · outbound

This paper cites Aby3: A mixed protocol framework for machine learning,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Aby3: A mixed protocol framework for machine learning,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:01:42.463054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d38b7dd4-0c36-403f-9205-59ddbc4533c7 · outbound

This paper cites The uci machine learning repository,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning The uci machine learning repository,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.561509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 39627efb-5f51-4eb1-89af-165f84e25f68 · outbound

This paper cites Give me some credit,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Give me some credit,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.550335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e65283c2-a1c3-4de3-ba6a-866ccad6fde7 · outbound

This paper cites A permutation network,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning A permutation network,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.538039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1a89e30b-df77-4f49-8336-44e45e1f91a8 · outbound

This paper cites The communication complexity of threshold private set intersection,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning The communication complexity of threshold private set intersection,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.526947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6d97bbcc-d8a0-4ba8-bad7-1dcf8d08caad · outbound

This paper cites Multi- party threshold private set intersection with sublinear communication,.

IDCloak: A Practical Secure Multi-party Dataset Join Framework for Vertical Privacy-preserving Machine Learning Multi- party threshold private set intersection with sublinear communication,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:42.515769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.