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
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.
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“Clifton et al. [117] describe a toolkit for various privacypreserving SMC-based data mining operations including secure sum computation using a secret random number.”
From A Survey of Self-Sovereign Identity Ecosystem (2021) · cites this paper as [117]
In the citing paper
“However, in this protocol, two adjacent parties can collude to compute the random number.”
From A Survey of Self-Sovereign Identity Ecosystem (2021) · cites this paper as [117]
Citations
Cites
Fast algorithms for mining association rules
Agrawal, R., & Srikant, R. (1998) · Cited by 11,362
Fast Algorithms for Mining Association Rules in Large Databases
Agrawal, R., & Srikant, R. (1994) · Very Large Data Bases · Cited by 9,454
Goldreich, O., Micali, S., & Wigderson, A. (1987) · Proceedings of the nineteenth annual ACM conference on Theory of computing - STOC '87 · doi:10.1145/28395.28420 · Cited by 3,590
Privacy-preserving data mining
Agrawal, R., & Srikant, R. (2000) · ACM SIGMOD Record · doi:10.1145/335191.335438 · Cited by 3,009
How to generate and exchange secrets
Yao, A. (1986) · 27th Annual Symposium on Foundations of Computer Science (sfcs 1986) · doi:10.1109/sfcs.1986.25 · Cited by 2,281
Privacy-preserving data mining
Agrawal, R., & Srikant, R. (2000) · Proceedings of the 2000 ACM SIGMOD international conference on Management of data · doi:10.1145/342009.335438 · Cited by 1,719
Pohlig, S., & Hellman, M. (1978) · IEEE Transactions on Information Theory · doi:10.1109/tit.1978.1055817 · Cited by 1,199
Privacy Preserving Data Mining
Lindell, Y., & Pinkas, B. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-44598-6_3 · Cited by 1,077
Privacy preserving association rule mining in vertically partitioned data
Vaidya, J., & Clifton, C. (2002) · Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/775047.775142 · Cited by 1,001
Self-citationPrivacy-preserving distributed mining of association rules on horizontally partitioned data
Clifton, C., Kantarcioglu, M., Clifton, C., & Member, S. (2010) · Cited by 888
Self-citation
Research works printed but not linked: 7
- 10.5555/645920.672836 · DOI
- 10.5555/645933.756665 · DOI
- 10.5555/382006.383194 · DOI
- 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.]]
- 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.]]
- 10.5555/850943.853036 · DOI
- B. Schneier. Applied Cryptography. John Wiley & Sons , 2 nd edition, 1995 .]] B. Schneier. Applied Cryptography. John Wiley & Sons, 2nd edition, 1995.]]
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An Algorithm for Privacy-Preserving Quantitative Association Rules Mining
Jing, W., Huang, L., Luo, Y., Xu, W., & Yao, Y. (2006) · IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) · doi:10.1109/dasc.2006.18 · Cited by 15
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Data Privacy Protection Based on Micro Aggregation with Dynamic Sensitive Attribute Updating
Shi, Y., Zhang, Z., Chao, H., & Shen, B. (2018) · Sensors · doi:10.3390/s18072307 · Cited by 15
Data privacy protection in multi-party clustering
Yang, W., & Huang, S. (2008) · Data & Knowledge Engineering · doi:10.1016/j.datak.2008.06.007 · Cited by 15
An Effective Method for Privacy Preserving Association Rule Mining
ZHANG, P. (2006) · Journal of Software · doi:10.1360/jos171764 · Cited by 15
Qiu, G., Tang, G., Li, C., Luo, L., Guo, D., & Shen, Y. (2023) · ACM Computing Surveys · doi:10.1145/3617589 · Cited by 14
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 ›
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