Perfectly Secure Oblivious RAM without Random Oracles

  • Ivan Damgård
  • Sigurd Meldgaard
  • Jesper Buus Nielsen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6597)

Abstract

We present an algorithm for implementing a secure oblivious RAM where the access pattern is perfectly hidden in the information theoretic sense, without assuming that the CPU has access to a random oracle. In addition we prove a lower bound on the amount of randomness needed for implementing an information theoretically secure oblivious RAM.

References

  1. 1.
    Ajtai, M., Komlós, J., Szemerédi, E.: An 0(n log n) sorting network. In: STOC 1983: Proceedings of the Fifteenth Annual ACM Symposium on Theory of Computing, pp. 1–9. ACM, New York (1983)CrossRefGoogle Scholar
  2. 2.
    Ajtai, M.: Oblivious rams without cryptographic assumptions. In: STOC 2010: Proceedings of the 42nd Annual ACM Symposium on Theory of Computing (2010) (to be published at STOC)Google Scholar
  3. 3.
    Batcher, K.E.: Sorting networks and their applications. In: AFIPS 1968 (Spring): Proceedings of the Spring Joint Computer Conference, April 30-May 2, pp. 307–314. ACM, New York (1968)CrossRefGoogle Scholar
  4. 4.
    Beame, P., Machmouchi, W.: Making RAMs Oblivious Requires Superlogarithmic Overhead. Electronic Colloquium on Computational Complexity (ECCC) 10(104) (2010)Google Scholar
  5. 5.
    Goldreich, O.: Towards a theory of software protection and simulation by oblivious rams. In: STOC 1987: Proceedings of the Nineteenth Annual ACM Symposium on Theory of Computing, pp. 182–194. ACM, New York (1987)CrossRefGoogle Scholar
  6. 6.
    Goldreich, O., Ostrovsky, R.: Software protection and simulation on oblivious rams. J. ACM 43(3), 431–473 (1996)CrossRefMATHMathSciNetGoogle Scholar

Copyright information

© International Association for Cryptologic Research 2011

Authors and Affiliations

  • Ivan Damgård
    • 1
  • Sigurd Meldgaard
    • 1
  • Jesper Buus Nielsen
    • 1
  1. 1.Department of Computer ScienceAarhus UniversityDenmark

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