The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
State-of-the-art in privacy preserving data mining
Abstract
We provide here an overview of the new and rapidly emerging research area of privacy preserving data mining. We also propose a classification hierarchy that sets the basis for analyzing the work which has been performed in this context. A detailed review of the work accomplished in this area is also given, along with the coordinates of each work to the classification hierarchy. A brief evaluation is performed, and some initial conclusions are made.
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Cites
A Mathematical Theory of Communication
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Mining association rules between sets of items in large databases
Agrawal, R., Imieliński, T., & Swami, A. (1993) · Proceedings of the 1993 ACM SIGMOD international conference on Management of data · doi:10.1145/170035.170072 · Cited by 14,907
Mining frequent patterns without candidate generation
Han, J., Pei, J., & Yin, Y. (2000) · ACM SIGMOD Record · doi:10.1145/335191.335372 · Cited by 6,402
Beyond Accuracy: What Data Quality Means to Data Consumers
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Validity of the single processor approach to achieving large scale computing capabilities
Amdahl, G. M. (1967) · Proceedings of the April 18-20, 1967, spring joint computer conference on - AFIPS '67 (Spring) · doi:10.1145/1465482.1465560 · Cited by 4,339
Anchoring Data Quality Dimensions in Ontological Foundations
Wand, Y., & Wang, R. Y. (1996) · Communications of the ACM · doi:10.1145/240455.240479 · Cited by 1,479
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
Tools for privacy preserving distributed data mining
Clifton, C., Kantarcioglu, M., Vaidya, J., Lin, X., & Zhu, M. Y. (2002) · ACM SIGKDD Explorations Newsletter · doi:10.1145/772862.772867 · Cited by 890
Cited by
Chen, M., Mao, S., & Liu, Y. (2014) · Mobile Networks and Applications · doi:10.1007/s11036-013-0489-0 · Cited by 2,913
Toward Scalable Systems for Big Data Analytics: A Technology Tutorial
Hu, H., Wen, Y., Chua, T.-S., & Li, X. (2014) · IEEE Access · doi:10.1109/access.2014.2332453 · Cited by 1,099
Information Security in Big Data: Privacy and Data Mining
Xu, L., Jiang, C., Wang, J., Yuan, J., & Ren, Y. (2014) · IEEE Access · doi:10.1109/access.2014.2362522 · Cited by 631
Liu, K., Kargupta, H., & Ryan, J. (2006) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2006.14 · Cited by 554
A General Survey of Privacy-Preserving Data Mining Models and Algorithms
Aggarwal, C. C., & Yu, P. S. (2008) · Advances in Database Systems · doi:10.1007/978-0-387-70992-5_2 · Cited by 469
Metadata
- Authors
- Verykios, V. S., Bertino, E., Fovino, I. N., Provenza, L. P., Saygin, Y., & Theodoridis, Y.
- Venue
- ACM SIGMOD Record
- Published
- 2004-03
- Volume
- 33
- Issue
- 1
- Pages
- 50-57
- ISSN
- 0163-5808 (ISSN-L)
- OpenAlex
- W2145747124
- Cited by
- 816
- References
- 9
- FWCI
- 45.07
- Type
- journal article
- Language
- en
- Open access
- closed
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- Verykios, V. S., Bertino, E., Fovino, I. N., Provenza, L. P., Saygin, Y., & Theodoridis, Y. (2004). State-of-the-art in privacy preserving data mining. ACM SIGMOD Record. https://doi.org/10.1145/974121.974131
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
