No One Size (PPM) Fits All: Towards Privacy in Stream Processing Systems-Reference-Cited by-同舟云学术

No One Size (PPM) Fits All: Towards Privacy in Stream Processing Systems

Published:2023-06-27 Issue: Volume: Page:
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Container-title:Proceedings of the 17th ACM International Conference on Distributed and Event-based Systems
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Author:

Fomichev Mikhail¹^ORCID,Luthra Manisha¹²^ORCID,Benndorf Maik³^ORCID,Agnihotri Pratyush¹^ORCID

Affiliation:

1. TU Darmstadt, Darmstadt, Germany

2. DFKI, Darmstadt, Germany

3. University of Oslo, Oslo, Norway

Publisher

ACM

Reference29 articles.

1. Sayan Biswas and Catuscia Palamidessi . 2022 . PRIVIC: A Privacy-preserving Method for Incremental Collection of Location Data. arXiv preprint arXiv:2206.10525 (2022). Sayan Biswas and Catuscia Palamidessi. 2022. PRIVIC: A Privacy-preserving Method for Incremental Collection of Location Data. arXiv preprint arXiv:2206.10525 (2022).

2. Cara Bloom. 2022. Privacy Threat Modeling. https://www.usenix.org/conference/pepr22/presentation/bloom. Cara Bloom. 2022. Privacy Threat Modeling. https://www.usenix.org/conference/pepr22/presentation/bloom.

3. Lukas Burkhalter , Anwar Hithnawi , Alexander Viand , Hossein Shafagh , and Sylvia Ratnasamy . 2020 . TimeCrypt: Encrypted Data Stream Processing at Scale with Cryptographic Access Control . In Proceedings of the 17th USENIX Symposium on Networked Systems Design and Implementation. 835--850 . Lukas Burkhalter, Anwar Hithnawi, Alexander Viand, Hossein Shafagh, and Sylvia Ratnasamy. 2020. TimeCrypt: Encrypted Data Stream Processing at Scale with Cryptographic Access Control. In Proceedings of the 17th USENIX Symposium on Networked Systems Design and Implementation. 835--850.

4. Castle: Continuously Anonymizing Data Streams;Cao Jianneng;IEEE Transactions on Dependable and Secure Computing,2010