Differential Privacy: A Survey of Results
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Citation edge evidence
- Federated Machine Learning→Differential Privacy: A Survey of ResultsLegacy edge — source detail unavailable
- Advances and Open Problems in Federated Learning→Differential Privacy: A Survey of ResultsLegacy edge — source detail unavailable
- A survey on federated learning→Differential Privacy: A Survey of ResultsLegacy edge — source detail unavailable
- Privacy-preserving data publishing→Differential Privacy: A Survey of ResultsLegacy edge — source detail unavailable
- Differential Privacy: A Survey of Results→k-ANONYMITY: A MODEL FOR PROTECTING PRIVACYLegacy edge — source detail unavailable
- Differential Privacy: A Survey of Results→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
- Differential Privacy: A Survey of Results→Differential PrivacyLegacy edge — source detail unavailable
- Differential Privacy: A Survey of Results→L -diversityLegacy edge — source detail unavailable
- Differential Privacy: A Survey of Results→Privacy-preserving data miningLegacy edge — source detail unavailable
- Differential Privacy: A Survey of Results→L-diversity: privacy beyond k-anonymityLegacy edge — source detail unavailable
- Differential Privacy: A Survey of Results→ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSIONLegacy edge — source detail unavailable
- Differential Privacy: A Survey of Results→Our Data, Ourselves: Privacy Via Distributed Noise GenerationLegacy edge — source detail unavailable
- Differential Privacy: A Survey of Results→Privacy-preserving data miningLegacy edge — source detail unavailable
- Our Data, Ourselves: Privacy Via Distributed Noise Generation→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
- Our Data, Ourselves: Privacy Via Distributed Noise Generation→Privacy-preserving data miningLegacy edge — source detail unavailable
- Calibrating Noise to Sensitivity in Private Data Analysis→Privacy-preserving data miningLegacy edge — source detail unavailable
- Calibrating Noise to Sensitivity in Private Data Analysis→k-ANONYMITY: A MODEL FOR PROTECTING PRIVACYLegacy edge — source detail unavailable
- ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSION→k-ANONYMITY: A MODEL FOR PROTECTING PRIVACYLegacy edge — source detail unavailable
- L -diversity→Privacy-preserving data miningLegacy edge — source detail unavailable
- L -diversity→L-diversity: privacy beyond k-anonymityLegacy edge — source detail unavailable
- L -diversity→k-ANONYMITY: A MODEL FOR PROTECTING PRIVACYLegacy edge — source detail unavailable
- L -diversity→Privacy-preserving data miningLegacy edge — source detail unavailable
- L-diversity: privacy beyond k-anonymity→Privacy-preserving data miningLegacy edge — source detail unavailable
- L-diversity: privacy beyond k-anonymity→L -diversityLegacy edge — source detail unavailable
- L-diversity: privacy beyond k-anonymity→k-ANONYMITY: A MODEL FOR PROTECTING PRIVACYLegacy edge — source detail unavailable
- Privacy-preserving data publishing→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
- Privacy-preserving data publishing→ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSIONLegacy edge — source detail unavailable
- Privacy-preserving data publishing→Privacy-preserving data miningLegacy edge — source detail unavailable
- Privacy-preserving data publishing→L -diversityLegacy edge — source detail unavailable
- Privacy-preserving data publishing→L-diversity: privacy beyond k-anonymityLegacy edge — source detail unavailable
- Privacy-preserving data publishing→k-ANONYMITY: A MODEL FOR PROTECTING PRIVACYLegacy edge — source detail unavailable
- Privacy-preserving data publishing→Differential PrivacyLegacy edge — source detail unavailable
- Privacy-preserving data publishing→Privacy-preserving data miningLegacy edge — source detail unavailable
- Differential Privacy→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
- Differential Privacy→ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSIONLegacy edge — source detail unavailable
- Differential Privacy→Privacy-preserving data miningLegacy edge — source detail unavailable
- Differential Privacy→Privacy-preserving data miningLegacy edge — source detail unavailable
- Federated Machine Learning→Privacy-preserving data miningLegacy edge — source detail unavailable
- Federated Machine Learning→k-ANONYMITY: A MODEL FOR PROTECTING PRIVACYLegacy edge — source detail unavailable
- Federated Machine Learning→Privacy-preserving data miningLegacy edge — source detail unavailable
- Advances and Open Problems in Federated Learning→Our Data, Ourselves: Privacy Via Distributed Noise GenerationLegacy edge — source detail unavailable
- Advances and Open Problems in Federated Learning→Calibrating Noise to Sensitivity in Private Data AnalysisLegacy edge — source detail unavailable
- Advances and Open Problems in Federated Learning→Privacy-preserving data miningLegacy edge — source detail unavailable
- Advances and Open Problems in Federated Learning→Federated Machine LearningLegacy edge — source detail unavailable
- A survey on federated learning→Federated Machine LearningLegacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY | 2002 | 8,585 |
| Calibrating Noise to Sensitivity in Private Data Analysis | 2006 | 7,210 |
| Differential Privacy | 2006 | 5,337 |
| L -diversity | 2007 | 3,628 |
| Privacy-preserving data mining | 2000 | 2,997 |
| L-diversity: privacy beyond k-anonymity | 2006 | 2,385 |
| ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSION | 2002 | 1,982 |
| Our Data, Ourselves: Privacy Via Distributed Noise Generation | 2006 | 1,826 |
| Privacy-preserving data mining | 2000 | 1,709 |
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Federated Machine Learning | 2019 | 6,228 |
| Advances and Open Problems in Federated Learning | 2020 | 5,383 |
| A survey on federated learning | 2021 | 1,847 |
| Privacy-preserving data publishing | 2010 | 1,651 |
Links
Topics
| Privacy-Preserving Technologies in Data | Computer Science |
| Cryptography and Data Security | Computer Science |
| Random Matrices and Applications | Mathematics |
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- supports50 reference(s) recorded.
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