The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Adaptively secure multi-party computation
Open accessAbstract
A fundamental problem in designing secure multi-party protocols is how to deal with adaptive adversaries (i.e., adversaries that may choose the corrupted parties during the course of the computation), in a setting where the channels are insecure and secure communication is achieved by cryptographic primitives based on the computational limitations of the adversary.
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Citations
Cites
A method for obtaining digital signatures and public-key cryptosystems
Rivest, R. L., Shamir, A., & Adleman, L. (1978) · Communications of the ACM · doi:10.1145/359340.359342 · Cited by 13,462
Goldreich, O., Micali, S., & Wigderson, A. (1987) · Proceedings of the nineteenth annual ACM conference on Theory of computing - STOC '87 · doi:10.1145/28395.28420 · Cited by 3,590
Self-citation
Cited by
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Mothukuri, V., Parizi, R. M., Pouriyeh, S., Huang, Y., Dehghantanha, A., & Srivastava, G. (2021) · Future Generation Computer Systems · doi:10.1016/j.future.2020.10.007 · Cited by 1,480
Property testing and its connection to learning and approximation
Goldreich, O., Goldwasser, S., & Ron, D. (1998) · Journal of the ACM · doi:10.1145/285055.285060 · Cited by 1,020
Self-citationSecure Multiparty Computation and Secret Sharing
Cramer, R., Damgård, I. B., & Nielsen, J. B. (2015) · doi:10.1017/cbo9781107337756 · Cited by 595
Differential Privacy for Deep and Federated Learning: A Survey
Ouadrhiri, A. E., & Abdelhadi, A. (2022) · IEEE Access · doi:10.1109/access.2022.3151670 · Cited by 445
Privacy preservation in federated learning: An insightful survey from the GDPR perspective
Truong, N., Sun, K., Wang, S., Guitton, F., & Guo, Y. (2021) · Computers & Security · doi:10.1016/j.cose.2021.102402 · Cited by 399
Metadata
- Authors
- Canetti, R., Feige, U., Goldreich, O., & Naor, M.
- Venue
- Proceedings of the twenty-eighth annual ACM symposium on Theory of computing - STOC '96
- Publisher
- ACM Press
- Published
- 1996
- Pages
- 639-648
- OpenAlex
- W2096430557
- Cited by
- 548
- References
- 2
- FWCI
- 11.33
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Adaptively secure multi-party computation. https://app.cochat.ai/papers/10.1145/237814.238015
- The paper
- Canetti, R., Feige, U., Goldreich, O., & Naor, M. (1996). Adaptively secure multi-party computation. Proceedings of the twenty-eighth annual ACM symposium on Theory of computing - STOC '96. https://doi.org/10.1145/237814.238015
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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.
