A Hybrid Approach for Privacy-Preserving Data Mining-Reference-Cited by-同舟云学术

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A Hybrid Approach for Privacy-Preserving Data Mining

Published:2018 Issue: Volume: Page:196-207
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Kundeti NagaPrasanthi,Rao M. V. P. Chandra Sekhara,Devarakonda Naga Raju,Thommandru Suresh

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-13-1810-8_20

Reference13 articles.

1. Li, X., Yan, Z., Zhang, P.: A review on privacy-preserving datamining. In: IEEE International Conference on Computer and Information Technology (2014)

2. Langheinrich, M.: Privacy in ubiquitous computing. In: Ubiquitous Computing Fundamentals, pp. 95–159. CRC Press (2009). ch. 3

3. Chen, K., Liu, L.: Geometric data perturbation for privacy preserving outsourced data mining. Knowl. Inf. Syst. 29, 657–695 (2011)

4. Westin, A.F.: Privacy and freedom. Wash. Lee Law Rev. 25(1), 166 (1968)

5. Advances in Database Systems;E Bertino,2008

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Boosted Hybrid Privacy Preserving Data Mining (BHPPDM) Technique to Increase Privacy and Accuracy;2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS);2023-02-02

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