- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
Saarbrücken, Universität des Saarlandes, Dissertation, 2023
- Keyword
-
Maschinelles Lernen
Kryptoanalyse
Privatsphäre
Datensicherung
Internet
Trusted Computing
- Event
-
Veröffentlichung
- (where)
-
Saarbrücken
- (who)
-
Saarländische Universitäts- und Landesbibliothek
- (when)
-
2023
- Creator
-
Xinlei, He
- Contributor
-
Zhang, Yang
- DOI
-
10.22028/D291-40392
- URN
-
urn:nbn:de:bsz:291--ds-403928
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
25.03.2025, 1:42 PM CET
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Xinlei, He
- Zhang, Yang
- Saarländische Universitäts- und Landesbibliothek
Time of origin
- 2023
Other Objects (12)
Cultures of privacy : paradigms, transformations, contestations
Emerging paradigms in machine learning
Understanding and assessment of privacy risks in machine learning systems
Privacy-preserving graph machine learning
Privacy impact assessment – a privacy protection improvement model?
Diffprivlib: Privacy-preserving machine learning with Scikit-learn: Train machine learning models with differential privacy guarantees
Deconstructing risk factors for predicting risk assessment in supply chains using machine learning
On the privacy risks of machine learning models
Towards a Complete Privacy Preserving Machine Learning Pipeline
Explainable machine learning for default privacy setting prediction
Secure Computation Protocols for Privacy-Preserving Machine Learning
Privacy Considerations for Risk-Based Authentication Systems
Cultures of privacy : paradigms, transformations, contestations
Emerging paradigms in machine learning
Understanding and assessment of privacy risks in machine learning systems
Privacy-preserving graph machine learning
Privacy impact assessment – a privacy protection improvement model?
Diffprivlib: Privacy-preserving machine learning with Scikit-learn: Train machine learning models with differential privacy guarantees
Deconstructing risk factors for predicting risk assessment in supply chains using machine learning
On the privacy risks of machine learning models
Towards a Complete Privacy Preserving Machine Learning Pipeline
Explainable machine learning for default privacy setting prediction
Secure Computation Protocols for Privacy-Preserving Machine Learning
Privacy Considerations for Risk-Based Authentication Systems
Cultures of privacy : paradigms, transformations, contestations
Emerging paradigms in machine learning
Understanding and assessment of privacy risks in machine learning systems
Privacy-preserving graph machine learning
Privacy impact assessment – a privacy protection improvement model?
Diffprivlib: Privacy-preserving machine learning with Scikit-learn: Train machine learning models with differential privacy guarantees
Deconstructing risk factors for predicting risk assessment in supply chains using machine learning
On the privacy risks of machine learning models
Towards a Complete Privacy Preserving Machine Learning Pipeline
Explainable machine learning for default privacy setting prediction
Secure Computation Protocols for Privacy-Preserving Machine Learning