CASTLE: Continuously Anonymizing Data Streams-Reference-Cited by-同舟云学术

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CASTLE: Continuously Anonymizing Data Streams

Published:2011-05 Issue:3 Volume:8 Page:337-352
ISSN:1545-5971
Container-title:IEEE Transactions on Dependable and Secure Computing
language:
Short-container-title:IEEE Trans. Dependable and Secure Comput.

Author:

Jianneng Cao ,Carminati B,Ferrari E,Kian-Lee Tan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx5/8858/5730203/05374415.pdf?arnumber=5374415

Cited by 82 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. Implementation and Performance Measurement of the SUHDSA (Secure, Useful, and High-performance Data-Stream Anonymization)+ Algorithm;2024 33rd International Conference on Computer Communications and Networks (ICCCN);2024-07-29

2. Efficient approximation and privacy preservation algorithms for real time online evolving data streams;World Wide Web;2024-01

3. Analyzing Continuous K$$_{s}$$-Anonymization for Smart Meter Data;Lecture Notes in Computer Science;2024

4. No One Size (PPM) Fits All: Towards Privacy in Stream Processing Systems;Proceedings of the 17th ACM International Conference on Distributed and Event-based Systems;2023-06-27

5. Privacy-preserving data (stream) mining techniques and their impact on data mining accuracy: a systematic literature review;Artificial Intelligence Review;2023-02-22

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