Privacy preserving data sharing and analysis for edge-based architectures-Reference-Cited by-同舟云学术

Privacy preserving data sharing and analysis for edge-based architectures

Published:2021-03-06 Issue: Volume: Page:
ISSN:1615-5262
Container-title:International Journal of Information Security
language:en
Short-container-title:Int. J. Inf. Secur.

Author:

Sheikhalishahi Mina,Saracino Andrea^ORCID,Martinelli Fabio,Marra Antonio La

Funder

Horizon 2020 Framework Programme

H2020 Excellent Science

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality,Information Systems,Software

Link

http://link.springer.com/content/pdf/10.1007/s10207-021-00542-x.pdf

Reference40 articles.

1. Ashok, V., Navuluri, K., Alhafdhi, A., Mukkamala, R.: Dataless data mining: association rules-based distributed privacy-preserving data mining. In: 12th International Conference on Information Technology—New Generations (ITNG), 2015, pp. 615–620 (2015)

2. Bertino, E., Lin, D., Jiang, W.: A survey of quantification of privacy preserving data mining algorithms. In: Privacy-preserving data mining, vol. 34, pp. 183–205. Springer (2008)

3. Bogan, E., English, J.: Benchmarking for Best Practices: Winning Through Innovative Adaptation (1994)

4. Brown, G., Pocock, A.C., Zhao, M., Luján, M.: Conditional likelihood maximisation: a unifying framework for information theoretic feature selection. J. Mach. Learn. Res. 13, 27–66 (2012)

5. Bunn, P., Ostrovsky, R.: Secure two-party k-means clustering. In: Proceedings of the 14th ACM Conference on Computer and Communications Security, pp. 486–497. CCS 07, ACM (2007)

Cited by 19 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. Further Insights: Balancing Privacy, Explainability, and Utility in Machine Learning-based Tabular Data Analysis;Proceedings of the 19th International Conference on Availability, Reliability and Security;2024-07-30

2. Real-time sharing algorithm of earthquake early warning data of hydropower station based on deep learning;Earth Science Informatics;2024-07-05

3. A divide-and-conquer approach to privacy-preserving high-dimensional big data release;Journal of Information Security and Applications;2024-06

4. Efficiently approaching vertical federated learning by combining data reduction and conditional computation techniques;Journal of Big Data;2024-05-28

5. A Scalable Vertical Federated Learning Framework for Analytics in the Cybersecurity Domain;2024 32nd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP);2024-03-20