Cited by 890Privacy-Preserving Technologies in DataCryptography and Data SecurityCloud Data Security Solutions

The DOI matches its Crossref record; 18 of the 19 references it cites were found in a registry or an index.

Tools for privacy preserving distributed data mining

Clifton, Chris, Kantarcioglu, Murat, Vaidya, Jaideep, Lin, Xiaodong, Zhu, Michael Y.·2002·ACM SIGKDD Explorations Newsletter

Abstract

Privacy preserving mining of distributed data has numerous applications. Each application poses different constraints: What is meant by privacy, what are the desired results, how is the data distributed, what are the constraints on collaboration and cooperative computing, etc. We suggest that the solution to this is a toolkit of components that can be combined for specific privacy-preserving data mining applications. This paper presents some components of such a toolkit, and shows how they can be used to solve several privacy-preserving data mining problems.

Overview

Integrity signals

Registry

Crossref · 10.1145/772862.772867

Cites

18 of 18 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Flagged first, then by citations

Show all 19 references

1 of the 19 references couldn’t be matched to a known paper.

Research works printed but not linked: 7

  1. 10.5555/645920.672836 · DOI
  2. 10.5555/645933.756665 · DOI
  3. 10.5555/382006.383194 · DOI
  4. A. Eisenberg . With false numbers, data crunchers try to mine the truth . New York Times , July 18 2002 .]] A. Eisenberg. With false numbers, data crunchers try to mine the truth. New York Times, July 18 2002.]]
  5. M. Hamblen . Privacy algorithms : Technology-based protections could make personal data impersonal . Computerworld , Oct. 14 2002 .]] M. Hamblen. Privacy algorithms: Technology-based protections could make personal data impersonal. Computerworld, Oct. 14 2002.]]
  6. 10.5555/850943.853036 · DOI
  7. B. Schneier. Applied Cryptography. John Wiley & Sons , 2 nd edition, 1995 .]] B. Schneier. Applied Cryptography. John Wiley & Sons, 2nd edition, 1995.]]

Cited by

Sorted by citations

Items 301–400 of 885

Metadata

Authors
Clifton, C., Kantarcioglu, M., Vaidya, J., Lin, X., & Zhu, M. Y.
Affiliations
  • Purdue University West Lafayette (US)
  • Purdue University, West Lafayette, IN
Venue
ACM SIGKDD Explorations Newsletter
Published
2002-12
Volume
4
Issue
2
Pages
28-34
ISSN
  • 1931-0145 (ISSN-L)
  • 1931-0153
OpenAlex
W2002352982
Cited by
890
References
19
Citations by year
2026: 7 · 2025: 6 · 2024: 12 · 2023: 14 · 2022: 27 · 2021: 38 · 2020: 31 · 2019: 40 · 2018: 46 · 2017: 41 · 2016: 51 · 2015: 57 · 2014: 70 · 2013: 68 · 2012: 50
FWCI
14.20
Type
journal article
Language
en
Open access
closed
Locations
ACM SIGKDD Explorations Newsletter (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
  • Physical Sciences › Computer Science › Computer Networks and Communications › Cryptography and Data Security
  • Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
Keywords
privacy-preserving data mining, distributed data mining, privacy definitions, collaborative computing, privacy-preserving association rule mining, privacy-preserving clustering

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review