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Probabilistic Analyses on Finding Optimal Combinations of Primality Tests in Real Applications

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Information Security Practice and Experience (ISPEC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 3439))

Abstract

Generating a prime is an iterative application of generating a random number r and testing the primality of r until r is a prime. Among them, the primality test on r is much more time-consuming than the random number generation and thus it occupies most of the running time of the prime generation. To reduce the running time of the primality test, real applications combine several primality test methods. The most widely used combination is the combination of the trial division and the probabilistic primality test. Although this combination is widely used in practice, few analyses were given on finding the optimal combination, i.e., on finding the optimal number of small primes used in trial division that minimizes the expected running time of this combination.

In this paper, we present probabilistic analyses on finding the optimal combinations of the trial division and the probabilistic primality test. Using these analyses, we present three optimal combinations. One is for the primality test and the others are for the safe primality test. The optimal combinations are universal in that they are presented as functions of div and ppt where div is the time required for dividing the random number r by a small prime and ppt is the time required for the probabilistic primality test of r. Thus, in any situation that div and ppt can be measured, the optimal combinations can be calculated from these functions. The experimental results show that our probabilistic analyses predict the optimal combinations well. The predicted optimal combinations can be used as useful guidelines in designing a primality or a safe primality test. The usefulness of the optimal combinations is more evident when the primality test is implemented on embedded systems or crypto-processors because finding optimal combinations using experiments is very time-consuming and inefficient.

This research was supported by the Program for the Training of Graduate Students in Regional Innovation which was conducted by the Ministry of Commerce, Industry and Energy of the Korean Government, and supported by KOSEF grant R01-2002-000-00589-0. Contact Author: dkkim@islab.ce.pusan.ac.kr.

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References

  1. Bosma, W., van der Hulst, M.P.: Faster primality testing. In: Brassard, G. (ed.) CRYPTO 1989. LNCS, vol. 435, pp. 652–656. Springer, Heidelberg (1990)

    Google Scholar 

  2. Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 2nd edn. MIT press, Cambridge (1991)

    Google Scholar 

  3. National Institute for Standards and Technology, Digital Signature Standard(DSS), Federal Register 56 169 (1991)

    Google Scholar 

  4. ElGamal, T.: A public key cryptosystem and a signature scheme based on discrete logarithms. IEEE Transactions on Information Theory 31(4), 469–472 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  5. Higgins, B.C.: The Rabin- Miller Probabilistic Primality Test: Some Results on the Number of Non-Witnesses to Compositeness, citeseer.nj.nec.com/400584.html

  6. Knuth, D.E.: The Art of Computer Programming: Seminumerical Algorithms. Addison-Wesley, USA (1981)

    MATH  Google Scholar 

  7. Miller, G.L.: Riemann’s Hypothesis and Tests for Primality. Journal of Computer Systems Science 13(3), 300–317 (1976)

    Article  MATH  Google Scholar 

  8. Menezes, A.J., van Oorschot, P.C., Vanstone, S.A.: Handbook of Applied Cryptography. CRC Press, Boca Raton (1997)

    MATH  Google Scholar 

  9. Park, H.: An Efficient Implementation of Safe Prime Generation. International Conference on Ubiquitous Computing, 241–243 (October 2003)

    Google Scholar 

  10. Pocklington, H.C.: The determination of the prime or composite nature of large numbers by Fermat’s theorem. Proc. of the Cambridge Philosophical Society 18, 29–30 (1914)

    MATH  Google Scholar 

  11. Rabin, M.O.: Probabilistic Algorithm for Primality Testing. Journal of Number Theory 12, 128–138 (1980)

    Article  MATH  MathSciNet  Google Scholar 

  12. Rivest, R.L., Shamir, A., Adleman, L.: A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM 21(2), 120–126 (1978)

    Article  MATH  MathSciNet  Google Scholar 

  13. Solovay, R., Strassen, V.: A fast Monte-Carlo test for primality. SIAM Journal on Computing 6, 84–85 (1977)

    Article  MATH  MathSciNet  Google Scholar 

  14. OpenSSL, http://www.openssl.org

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© 2005 Springer-Verlag Berlin Heidelberg

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Park, H., Park, S.K., Kwon, KR., Kim, D.K. (2005). Probabilistic Analyses on Finding Optimal Combinations of Primality Tests in Real Applications. In: Deng, R.H., Bao, F., Pang, H., Zhou, J. (eds) Information Security Practice and Experience. ISPEC 2005. Lecture Notes in Computer Science, vol 3439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31979-5_7

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  • DOI: https://doi.org/10.1007/978-3-540-31979-5_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25584-0

  • Online ISBN: 978-3-540-31979-5

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