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Random Number Generation using SDRAM  

Pyo, Chang-Woo (홍익대학교 컴퓨터공학과)
Abstract
Cryptographic keys for security should be generated by true random number generators that apply irreversible hashing algorithms to initial values taken from a random source. As DRAM shows randomness in its access latency, it can be used as a random source. However, systems with synchronous DRAM (SDRAM) do not easily expose such randomness resulting in highly clustered random numbers. We resolved this problem by using the xor instruction. Statistical testing shows that the generated random bits have the quality comparable to true random bit sequences. The performance of bit generation is at the order of 100 Kbits/sec. Since the proposed random number generation requires neither external devices nor any special circuits, this method may be used in any computing device that employs DRAM.
Keywords
Cryptographic key; random number generation; DRAM; access latency; SDRAM;
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1 B. Schneier, Applied Cryptography: Protocols, Algorithms, and Source Code in C, 2nd ed., pp.233- 234, John Wiley & Sons, New York, 1996.
2 B. Jacob, S. Ng, D. Wang, Memory System: Cache, DRAM, Disk, pp.465-480, Morgan-Kaufman Publishers Inc., Massachusetts, 2007.
3 B. Schneier, Applied Cryptography: Protocols, Algorithms, and Source Code in C, 2nd ed., p.425, John Wiley & Sons, New York, 1996.
4 A. Rukhin, J. Soto, etal., A statistical test suite for random and pseudorandom number generators for cryptographic applications, Revised, L. Bassham III, Special Publication SP 800-22 rev.1, National Institute of Standards and Technology (NIST), Aug. 2008.
5 S. Kim, K. Umeno, A. Hasegawa, Corrections of the NIST statistical test suite for randomness. Cryptology ePrint Archive, Report 2004/018, 2004.
6 W. Killmann, W. Schindler, "A Design for a Physical RNG with Robust Entropy Estimators," CHES 2008, Lecture Notes in Computer Science, vol.5154, pp.146-163, 2008.
7 A. Alkassar, T. Nicolay, and M. Rohe, "Obtaining true-random binary numbers from a weak radioactive source," ICCSA (2), Lecture Notes in Computer Science, vol.3481, pp.634-646, 2005.
8 M. Haahr, RANDOM.ORG, http://www.random.org, Trinity College, Ireland, 1998.
9 L. Noll, LAVARND, http://www.lavarnd.org, 2000.
10 M. Dichtl and J. Golic, "High-Speed True Random Number Generation with Logic Gates Only," CHES 2007, Lecture Notes in Computer Science, vol.4727, pp.45-62, 2007.
11 I. Vasyltsov, E. Hambardzumyan, Y. Kim, B. Karpinskyy, "Fast Digital TRNG based on Metastable Ring Oscillator," CHES 2008, Lecture Notes in Computer Science, vol.5154, pp.164-180, 2008.
12 D. Davis, R. Ihaka, and P. Fenstermacher, "Cryptographic randomness from air turbulence in disk drives," CRYPTO '94: Proc. of the 14th Annual International Cryptology Conference on Advances in Cryptology, pp.114-120, Springer-Verlag, 1994.
13 A. SEZNEC and N. SENDRIER, "HAVEGE: A User-Level Software Heuristic for Generating Empirically Strong Random Numbers," ACM Transactions on Modeling and Computer Simulation, vol.13, no.4, pp.334-346, 2003.   DOI   ScienceOn
14 V. Cuppu, B. Jacob, B. Davis, T. Mudge, "A Performance Comparison of Contemporary DRAM Architectures," 26th Annual International Symposium on Computer Architecture (ISCA'99), vol.27, no.2, pp.222-232, 1999.