The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Cryptographic Primitives Based on Hard Learning Problems
Open accessAbstract
Modern cryptography has had considerable impact on the development of computational learning theory. Virtually every intractability result in Valiant’s model [13] (which is representation-independent in the sense that it does not rely on an artificial syntactic restriction on the learning algorithm’s hypotheses) has at its heart a cryptographic construction [4, 9, 1, 10]. In this paper, we give results in the reverse direction by showing how to construct several cryptographic primitives based on certain assumptions on the difficulty of learning. In doing so, we develop further a line of thought introduced by Impagliazzo and Levin [6].
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Citations
Cites
Valiant, L. G. (1984) · Communications of the ACM · doi:10.1145/1968.1972 · Cited by 3,279
How to construct random functions
Goldreich, O., Goldwasser, S., & Micali, S. (1986) · Journal of the ACM · doi:10.1145/6490.6503 · Cited by 2,115
On the inherent intractability of certain coding problems (Corresp.)
Berlekamp, E., McEliece, R., & van Tilborg, H. (1978) · IEEE Transactions on Information Theory · doi:10.1109/tit.1978.1055873 · Cited by 1,523
Theory and application of trapdoor functions
Yao, A. C.-C. (1982) · doi:10.1109/sfcs.1982.95 · Cited by 1,008
Theory and application of trapdoor functions
Yao, A. C. (1982) · 23rd Annual Symposium on Foundations of Computer Science (sfcs 1982) · doi:10.1109/sfcs.1982.45 · Cited by 968
Cryptographic limitations on learning Boolean formulae and finite automata
Kearns, M., & Valiant, L. (1994) · Journal of the ACM · doi:10.1145/174644.174647 · Cited by 733
Self-citationPseudo-random generation from one-way functions
Impagliazzo, R., Levin, L. A., & Luby, M. (1989) · Proceedings of the twenty-first annual ACM symposium on Theory of computing - STOC '89 · doi:10.1145/73007.73009 · Cited by 724
Crytographic limitations on learning Boolean formulae and finite automata
Kearns, M., & Valiant, L. G. (1989) · Proceedings of the twenty-first annual ACM symposium on Theory of computing - STOC '89 · doi:10.1145/73007.73049 · Cited by 266
Self-citationWhen won't membership queries help?
Angluin, D., & Kharitonov, M. (1991) · Proceedings of the twenty-third annual ACM symposium on Theory of computing - STOC '91 · doi:10.1145/103418.103420 · Cited by 190
Efficient noise-tolerant learning from statistical queries
Kearns, M. (1993) · Proceedings of the twenty-fifth annual ACM symposium on Theory of computing - STOC '93 · doi:10.1145/167088.167200 · Cited by 173
Self-citation
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On lattices, learning with errors, random linear codes, and cryptography
Regev, O. (2009) · Journal of the ACM · doi:10.1145/1568318.1568324 · Cited by 2,315
On lattices, learning with errors, random linear codes, and cryptography
Regev, O. (2005) · Proceedings of the thirty-seventh annual ACM symposium on Theory of computing · doi:10.1145/1060590.1060603 · Cited by 2,313
On-the-fly multiparty computation on the cloud via multikey fully homomorphic encryption
López-Alt, A., Tromer, E., & Vaikuntanathan, V. (2012) · Proceedings of the forty-fourth annual ACM symposium on Theory of computing · doi:10.1145/2213977.2214086 · Cited by 910
On Ideal Lattices and Learning with Errors over Rings
Lyubashevsky, V., Peikert, C., & Regev, O. (2013) · Journal of the ACM · doi:10.1145/2535925 · Cited by 836
FHEW: Bootstrapping Homomorphic Encryption in Less Than a Second
Ducas, L., & Micciancio, D. (2015) · Lecture Notes in Computer Science · doi:10.1007/978-3-662-46800-5_24 · Cited by 745
Metadata
- Authors
- Blum, A., Furst, M., Kearns, M., & Lipton, R. J.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 1994
- Pages
- 278-291
- ISSN
- 0302-9743 (ISSN-L)
- OpenAlex
- W1856342626
- Cited by
- 332
- References
- 14
- FWCI
- 3.33
- Type
- conference paper
- Language
- en
- Open access
- green
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- Blum, A., Furst, M., Kearns, M., & Lipton, R. J. (1994). Cryptographic Primitives Based on Hard Learning Problems. Lecture Notes in Computer Science. https://doi.org/10.1007/3-540-48329-2_24
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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).
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