Paper Citation Record · LEDGER

SKALD: Scalable K-Anonymisation for Large Datasets

As of 19 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2505.03529.

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

pith.paper-citation-record.v1
2505.03529 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:54:14.015192Z

measured 19 of 19 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

19 of 19 outbound references displayed

verified exact3
verified fuzzy11
unresolved4
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7ebcb645-17a6-4055-8179-de65d7f62f16 · outbound

This paper cites Ex- posed! A survey of attacks on private data,.

SKALD: Scalable K-Anonymisation for Large Datasets Ex- posed! A survey of attacks on private data,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.401387Z

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 d4900bc3-b345-446b-8d21-697ddeab7b06 · outbound

This paper cites The 2010 Census Confidentiality Protections Failed, Here’s How and Why,.

SKALD: Scalable K-Anonymisation for Large Datasets The 2010 Census Confidentiality Protections Failed, Here’s How and Why,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.388415Z

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 07dd9674-81c7-423e-825c-370ecbd16e0d · outbound

This paper cites Anonymization: The imperfect science of using data while preserving privacy,.

SKALD: Scalable K-Anonymisation for Large Datasets Anonymization: The imperfect science of using data while preserving privacy,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T23:54:13.949374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 455becf6-d194-42b7-90ba-086efe00378a · outbound

This paper cites [Online].

SKALD: Scalable K-Anonymisation for Large Datasets [Online]

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.375831Z

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 1119e4d4-a8a0-4006-8aaf-73f84b40a7fc · outbound

This paper cites k-anonymity: A model for protecting privacy,.

SKALD: Scalable K-Anonymisation for Large Datasets k-anonymity: A model for protecting privacy,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.363004Z

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 4cafd7e4-0315-4761-bf15-0f017f8a1ec8 · outbound

This paper cites The Future of Data Protection in India - Part 1: A Roadmap for Regulators,.

SKALD: Scalable K-Anonymisation for Large Datasets The Future of Data Protection in India - Part 1: A Roadmap for Regulators,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.349589Z

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 40726af5-6982-4eca-9d52-7d39a9df35ed · outbound

This paper cites 1–88, May 4, 2016.

SKALD: Scalable K-Anonymisation for Large Datasets 1–88, May 4, 2016

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.336463Z

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 1891c55d-483b-4128-bf4a-6d5e878b9c76 · outbound

This paper cites Building a privacy web with spider - secure pipeline for infor- mation de-identification with end-to-end encryption,.

SKALD: Scalable K-Anonymisation for Large Datasets Building a privacy web with spider - secure pipeline for infor- mation de-identification with end-to-end encryption,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T23:54:13.971116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8db555f7-ca52-4420-b537-e41b1d8da83e · outbound

This paper cites A Globally Optimal k-Anonymity Method for the De-Identification of Health Data,.

SKALD: Scalable K-Anonymisation for Large Datasets A Globally Optimal k-Anonymity Method for the De-Identification of Health Data,

Reference 9

Resolution: verified exact; doi, observed 2026-08-15T23:54:14.086573Z

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 4944f4bc-3bad-4079-a2dc-7a6263dfbce3 · outbound

This paper cites Lightning: Utility-driven anonymiza- tion of high-dimensional data,.

SKALD: Scalable K-Anonymisation for Large Datasets Lightning: Utility-driven anonymiza- tion of high-dimensional data,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.322404Z

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 787dbde6-7cb3-4f73-9f3a-f320fabcfa05 · outbound

This paper cites Achieving k-anonymity privacy protection using generalization and suppression,.

SKALD: Scalable K-Anonymisation for Large Datasets Achieving k-anonymity privacy protection using generalization and suppression,

Reference 11

Resolution: verified exact; doi, observed 2026-08-15T23:54:14.073896Z

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 545b87de-716a-4661-b919-3f237489732c · outbound

This paper cites A scalable software solution for anonymizing high- dimensional biomedical data,.

SKALD: Scalable K-Anonymisation for Large Datasets A scalable software solution for anonymizing high- dimensional biomedical data,

Reference 12

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T23:54:14.307171Z

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 c6d9b113-3b6d-4681-9348-82e926aa3237 · outbound

This paper cites De-identifying government datasets:.

SKALD: Scalable K-Anonymisation for Large Datasets De-identifying government datasets:

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T23:54:13.991030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 411de6b3-18e2-4a82-b441-ee4ffb6f2821 · outbound

This paper cites Efficient Algorithms for Mask- ing and Finding Quasi-Identifiers,.

SKALD: Scalable K-Anonymisation for Large Datasets Efficient Algorithms for Mask- ing and Finding Quasi-Identifiers,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.292840Z

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 bf4fb4d0-1318-4025-a5f7-d449e5894fda · outbound

This paper cites Simple Demographics Often Identify Peo- ple Uniquely,.

SKALD: Scalable K-Anonymisation for Large Datasets Simple Demographics Often Identify Peo- ple Uniquely,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.279187Z

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 f4c24b4d-3d5a-49f1-87d5-108340cf2890 · outbound

This paper cites On the complexity of optimal k-anonymity,.

SKALD: Scalable K-Anonymisation for Large Datasets On the complexity of optimal k-anonymity,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T23:54:14.003209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1224f9e3-35ed-4603-97e9-7ad587c7174e · outbound

This paper cites Incognito: Efficient Full-Domain K-Anonymity,.

SKALD: Scalable K-Anonymisation for Large Datasets Incognito: Efficient Full-Domain K-Anonymity,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.265200Z

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 832d697c-a55b-4d41-9030-cca19d52b54d · outbound

This paper cites Flash: Efficient, stable and optimal k- anonymity,.

SKALD: Scalable K-Anonymisation for Large Datasets Flash: Efficient, stable and optimal k- anonymity,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:54:14.251218Z

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 87e598ff-fb05-46a6-a778-144352f947f8 · outbound

This paper cites an unresolved cited work.

SKALD: Scalable K-Anonymisation for Large Datasets Unresolved cited work

Reference 2012

Resolution: verified exact; doi, observed 2026-08-15T23:54:14.049591Z

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.