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On cryptography with auxiliary input
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Annual ACM Symposium on Theory of Computing archive
Proceedings of the 41st annual ACM symposium on Theory of computing table of contents
Bethesda, MD, USA
SESSION: Crypto II table of contents
Pages 621-630  
Year of Publication: 2009
ISBN:978-1-60558-506-2
Authors
Yevgeniy Dodis  NYU, NY, NY, USA
Yael Tauman Kalai  Microsoft, Cambridge , MA, USA
Shachar Lovett  Weizmann Institute, Rehovot, Israel
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
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ABSTRACT

We study the question of designing cryptographic schemes which are secure even if an arbitrary function f(sk) of the secret key is leaked, as long as the secret key sk is still (exponentially) hard to compute from this auxiliary input. This setting of auxiliary input is more general than the more traditional setting, which assumes that some of information about the secret key sk may be leaked, but sk still has high min-entropy left. In particular, we deal with situations where f(sk) information-theoretically determines the entire secret key sk.

As our main result, we construct CPA/CCA secure symmetric encryption schemes that remain secure with exponentially hard-to-invert auxiliary input. We give several applications of such schemes. * We construct an average-case obfuscator for the class of point functions, which remains secure with exponentially hard-to-invert auxiliary input, and is reusable. * We construct a reusable and robust extractor that remains secure with exponentially hard-to-invert auxiliary input. Our results rely on a new cryptographic assumption, Learning Subspace-with-Noise (LSN), which is related to the well known Learning Parity-with-Noise (LPN) assumption.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Yevgeniy Dodis: colleagues
Yael Tauman Kalai: colleagues
Shachar Lovett: colleagues