Frequency Oracle for Sensitive Data Monitoring Article Swipe
As data privacy issues grow, finding the best privacy preservation algorithm for each situation is increasingly essential. This research has focused on understanding the frequency oracles (FO) privacy preservation algorithms. FO conduct the frequency estimation of any value in the domain. The aim is to explore how each can be best used and recommend which one to use with which data type. We experimented with different data scenarios and federated learning settings. Results showed clear guidance on when to use a specific algorithm.
Related Topics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://www.osti.gov/biblio/2438986
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4402623156
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4402623156Canonical identifier for this work in OpenAlex
- Title
-
Frequency Oracle for Sensitive Data MonitoringWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-09-04Full publication date if available
- Authors
-
Richard Sances, Olivera Kotevska, Paul LaiuList of authors in order
- Landing page
-
https://www.osti.gov/biblio/2438986Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.osti.gov/biblio/2438986Direct OA link when available
- Concepts
-
Oracle, Computer science, Environmental science, Remote sensing, Geology, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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