Hybrid Solution for Privacy-Preserving Data Mining on the Cloud Computing-Reference-Cited by-同舟云学术

Hybrid Solution for Privacy-Preserving Data Mining on the Cloud Computing

Published:2019-11-02 Issue: Volume: Page:748-758
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Osman Huda,Maarof Mohd Aizaini,Siraj Maheyzah Md

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-33582-3_70

Reference32 articles.

1. Samanthula, B.K., Elmehdwi, Y., Jiang, W.: k-nearest neighbor classification over semantically secure encrypted relational data. IEEE Trans. Knowl. Data Eng. 27(5), 1261–1273 (2015)

2. Suresh, S., Huang, H., Kim, H.J.: Scheduling in compute cloud with multiple data banks using divisible load paradigm. IEEE Trans. Aerosp. Electron. Syst. 51(2), 1288–1297 (2015)

3. Zhang, L., Yan, Y., Wang, W., Hao, X.: Finding quasi-identifiers for k-anonymity model by the set of cut-vertex (2018)

4. Zhang, H., Zhou, Z., Ye, L., Du, X.: Towards privacy preserving publishing of set-valued data on hybrid cloud (2018). https://ieeexplore.ieee.org

5. Aldeen Yousra, S., Mazleena, S.: A new heuristic anonymization technique for privacy preserved datasets publication on cloud computing. J. Phys: Conf. Ser. 1003, 012030 (2018)

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1. A Cloud-Based Platform for Encrypted Data Mining as a Service;2023 Mexican International Conference on Computer Science (ENC);2023-09-11

2. HAC: Model for Privacy-Preserving Outsourced Data Over Cloud;2021 3rd International Cyber Resilience Conference (CRC);2021-01-29