The DOI matches its Crossref record; 32 of the 33 references it cites were found in a registry or an index.
Public-Key Cryptosystems Based on Composite Degree Residuosity Classes
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In the citing paper
“Depending on the attacker's objective, poisoning attacks can be broadly classified into two categories: 1) untargeted poisoning attacks [123], [124], [125], [70], [67]; and 2) targeted poisoning attacks [126], [127], [35], [36], [128], [129], [130], [131].”
From Privacy and Robustness in Federated Learning: Attacks and Defenses (2024) · cites this paper as [126]
Citations
Cites
New directions in cryptography
Diffie, W., & Hellman, M. (1976) · IEEE Transactions on Information Theory · doi:10.1109/tit.1976.1055638 · Cited by 14,713
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
A method for obtaining digital signatures and public-key cryptosystems
Rivest, R. L., Shamir, A., & Adleman, L. (1983) · Communications of the ACM · doi:10.1145/357980.358017 · Cited by 13,012
A public key cryptosystem and a signature scheme based on discrete logarithms
Elgamal, T. (1985) · IEEE Transactions on Information Theory · doi:10.1109/tit.1985.1057074 · Cited by 8,059
Bellare, M., & Rogaway, P. (1993) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/168588.168596 · Cited by 4,695
A Public-Key Cryptosystem Based On Algebraic Coding Theory
McEliece, R. J. (1978) · Deep Space Network Progress Report · Cited by 1,578
Mollin, R. A. (2005) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420035087-10 · Cited by 914
Hiding information and signatures in trapdoor knapsacks
Merkle, R. C., & Hellman, M. E. (1978) · IEEE Transactions on Information Theory · doi:10.1109/tit.1978.1055927 · Cited by 825
A secure and optimally efficient multi‐authority election scheme
Cramer, R., Gennaro, R., & Schoenmakers, B. (1997) · European Transactions on Telecommunications · doi:10.1002/ett.4460080506 · Cited by 788
A new public-key cryptosystem as secure as factoring
Okamoto, T., & Uchiyama, S. (1998) · Lecture notes in computer science · doi:10.1007/bfb0054135 · Cited by 674
Research works printed but not linked: 2
- S. Goldwasser and S. Micali, Probabilistic Encryption, JCSS Vol. 28 No 2, pp. 270–299, 1984.
- J. Patarin, The Oil and Vinegar Algorithm for Signatures, presented at the Dagstuhl Workshop on Cryptography, 1997.
Cited by
Sorted by citations
Items 1,001–1,010 of 1,010
APFed: Anti-Poisoning Attacks in Privacy-Preserving Heterogeneous Federated Learning
Chen, X., Yu, H., Jia, X., & Yu, X. (2023) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2023.3315125 · Cited by 50
TollsOnly Please—Homomorphic Encryption for Toll Transponder Privacy in Internet of Vehicles
Karim, H., & Rawat, D. B. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3056240 · Cited by 43
Federated learning‐based trajectory prediction model with privacy preserving for intelligent vehicle
Han, M., Xu, K., Ma, S., Li, A., & Jiang, H. (2022) · International Journal of Intelligent Systems · doi:10.1002/int.22987 · Cited by 37
Kumari, K. A., Sharma, A., Chakraborty, C., & Ananyaa, M. (2022) · Big Data · doi:10.1089/big.2021.0012 · Cited by 36
Lightweight Privacy and Security Computing for Blockchained Federated Learning in IoT
Fan, M., Ji, K., Zhang, Z., Yu, H., & Sun, G. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3267112 · Cited by 37
From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks
Geng, X., Wang, Z., Chen, C., Xu, Q., Xu, K., Jin, C., Gupta, M., Yang, X., Chen, Z., Sabry Aly, M. M., et al. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3394494 · Cited by 26
FREED: An Efficient Privacy-Preserving Solution for Person Re-IDentification
Zhao, B., Li, Y., Liu, X., Pang, H. H., & Deng, R. H. (2022) · 2022 IEEE Conference on Dependable and Secure Computing (DSC) · doi:10.1109/dsc54232.2022.9888863 · Cited by 23
A Survey on Secure Computation Based on Homomorphic Encryption in Vehicular Ad Hoc Networks
Sun, X., Yu, F. R., Zhang, P., Xie, W., & Peng, X. (2020) · Sensors · doi:10.3390/s20154253 · Cited by 23
Homomorphic encryption based privacy-aware intelligent forwarding mechanism for NDN-VANET
Guo, X., Wang, B., Jiang, Y., Zhang, D., & Cao, L. (2023) · Computer Science and Information Systems · doi:10.2298/csis220210051g · Cited by 2
CrypTen: Secure Multi-Party Computation Meets Machine Learning
Knott, B., Venkataraman, S., Hannun, A., Sengupta, S., Ibrahim, M., & van der Maaten, L. (2021) · arXiv · doi:10.48550/arxiv.2109.00984 · Cited by 257
Metadata
- Authors
- Paillier, P.
- Affiliations
- Télécom Paris (FR)
- Corresponding author
- Paillier, Pascal
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2007-10-10
- Pages
- 223-238
- OpenAlex
- W2132172731
- Cited by
- 7,250
- References
- 33
- Citations by year
- 2026: 199 · 2025: 370 · 2024: 434 · 2023: 429 · 2022: 445 · 2021: 493 · 2020: 476 · 2019: 469 · 2018: 493 · 2017: 447 · 2016: 398 · 2015: 363 · 2014: 336 · 2013: 344 · 2012: 263
- FWCI
- 147.26
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Cryptography and Data Security
- Physical Sciences › Computer Science › Information Systems › Cryptography and Residue Arithmetic
- Physical Sciences › Mathematics › Discrete Mathematics and Combinatorics › Coding theory and cryptography
- Keywords
- public-key cryptography, trapdoor permutations, homomorphic encryption, probabilistic encryption, modular arithmetic, standard model security
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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