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Immunizing Encryption Schemes from Decryption Errors

  • Cynthia Dwork
  • Moni Naor
  • Omer Reingold
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3027)

Abstract

We provide methods for transforming an encryption scheme susceptible to decryption errors into one that is immune to these errors. Immunity to decryption errors is vital when constructing non-malleable and chosen ciphertext secure encryption schemes via current techniques; in addition, it may help defend against certain cryptanalytic techniques, such as the attack of Proos [33] on the NTRU scheme.

When decryption errors are very infrequent, our transformation is extremely simple and efficient, almost free. To deal with significant error probabilities, we apply amplification techniques translated from a related information theoretic setting. These techniques allow us to correct even very weak encryption schemes where in addition to decryption errors, an adversary has substantial probability of breaking the scheme by decrypting random messages (without knowledge of the secret key). In other words, under these weak encryption schemes, the only guaranteed difference between the legitimate recipient and the adversary is in the frequency of decryption errors. All the above transformations work in a standard cryptographic model; specifically, they do not rely on a random oracle. We also consider the random oracle model, where we give a simple transformation from a one-way encryption scheme which is error-prone into one that is immune to errors.

We conclude that error-prone cryptosystems can be used in order to create more secure cryptosystems.

Keywords

Encryption Scheme Random Oracle Decryption Algorithm Pseudorandom Generator Parallel Repetition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Cynthia Dwork
    • 1
  • Moni Naor
    • 2
  • Omer Reingold
    • 2
  1. 1.Microsoft Research, SVCMountain ViewUSA
  2. 2.Weizmann Institute of ScienceRehovotIsrael

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