The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Broadening the Scope of Differential Privacy Using Metrics
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Citations
Cites
Calibrating Noise to Sensitivity in Private Data Analysis
Dwork, C., McSherry, F., Nissim, K., & Smith, A. (2006) · Lecture Notes in Computer Science · doi:10.1007/11681878_14 · Cited by 7,272
Dwork, C. (2006) · Lecture Notes in Computer Science · doi:10.1007/11787006_1 · Cited by 5,291
On observing nondeterminism and concurrency
Hennessy, M., & Milner, R. (1980) · Lecture Notes in Computer Science · doi:10.1007/3-540-10003-2_79 · Cited by 4,492
Dwork, C., Hardt, M., Pitassi, T., Reingold, O., & Zemel, R. (2012) · Proceedings of the 3rd Innovations in Theoretical Computer Science Conference · doi:10.1145/2090236.2090255 · Cited by 3,501
Our Data, Ourselves: Privacy Via Distributed Noise Generation
Dwork, C., Kenthapadi, K., McSherry, F., Mironov, I., & Naor, M. (2006) · Lecture Notes in Computer Science · doi:10.1007/11761679_29 · Cited by 1,835
De-anonymizing Social Networks
Narayanan, A., & Shmatikov, V. (2009) · 2009 30th IEEE Symposium on Security and Privacy · doi:10.1109/sp.2009.22 · Cited by 1,301
Towards Sharp Inapproximability For Any 2-CSP
Austrin, P. (2007) · 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07) · doi:10.1109/focs.2007.41 · Cited by 1,294
Hansmann, U., Stöber, T., Merk, L., & Nicklous, M. S. (2003) · Cited by 1,168
Geo-indistinguishability: differential privacy for location-based systems
Andrés, M. E., Bordenabe, N. E., Chatzikokolakis, K., & Palamidessi, C. (2013) · Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security - CCS '13 · doi:10.1145/2508859.2516735 · Cited by 1,059
Self-citationSmooth sensitivity and sampling in private data analysis
Nissim, K., Raskhodnikova, S., & Smith, A. (2007) · Proceedings of the thirty-ninth annual ACM symposium on Theory of computing · doi:10.1145/1250790.1250803 · Cited by 974
Cited by
Certified Robustness to Adversarial Examples with Differential Privacy
Lecuyer, M., Atlidakis, V., Geambasu, R., Hsu, D., & Jana, S. (2019) · 2019 IEEE Symposium on Security and Privacy (SP) · doi:10.1109/sp.2019.00044 · Cited by 750
Differential Privacy Techniques for Cyber Physical Systems: A Survey
Hassan, M. U., Rehmani, M. H., & Chen, J. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2944748 · Cited by 564
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy
Ponomareva, N., Hazimeh, H., Kurakin, A., Xu, Z., Denison, C., McMahan, H. B., Vassilvitskii, S., Chien, S., & Thakurta, A. G. (2023) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.14649 · Cited by 166
Clustered federated learning with adaptive local differential privacy on heterogeneous IoT data
He, Z., Wang, L., & Cai, Z. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3299947 · Cited by 143
Location privacy models in mobile applications: Conceptual view and research directions
Damiani, M. L. (2014) · GeoInformatica · doi:10.1007/s10707-014-0205-7 · Cited by 34
Metadata
- Authors
- Chatzikokolakis, K., Andrés, M. E., Bordenabe, N. E., & Palamidessi, C.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2013
- Pages
- 82-102
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1658920975
- Cited by
- 340
- References
- 31
- FWCI
- 10.19
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Broadening the Scope of Differential Privacy Using Metrics. https://app.cochat.ai/papers/10.1007/978-3-642-39077-7_5
- The paper
- Chatzikokolakis, K., Andrés, M. E., Bordenabe, N. E., & Palamidessi, C. (2013). Broadening the Scope of Differential Privacy Using Metrics. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-39077-7_5
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
