Finding Differential Paths in ARX Ciphers through Nested Monte-Carlo Search

Authors

  • Ashutosh Dhar Dwivedi Institute of Computer Science, Polish Academy of Sciences
  • Paweł Morawiecki Institute of Computer Science, Polish Academy of Sciences
  • Sebastian Wójtowicz Institute of Computer Science, Polish Academy of Sciences

Abstract

We propose the adaptation of Nested Monte-Carlo Search algorithm for finding differential trails in the class of ARX ciphers. The practical application of the algorithm is demonstrated on round-reduced variants of block ciphers from the SPECK family. More specifically, we report the best differential trails,up to 9 rounds, for SPECK32.

References

R. Beaulieu, D. Shors, J. Smith, S. Treatman-Clark, B. Weeks, and

L. Wingers, “The SIMON and SPECK families of lightweight block

ciphers,” IACR Cryptology ePrint Archive, vol. 2013, p. 404, 2013.

N. Ferguson, B. S. S. Lucks, D. Whiting, M. Bellare, T. Kohno, J. Callas,

and J. Walker., “The Skein Hash Function Family,” submission to the

NIST SHA-3 Competition (Round 2), 2009.

A. Biryukov and V. Velichkov, “Automatic search for differential trails

in ARX ciphers,” in Topics in Cryptology - CT-RSA 2014 - The Cryptographer’s Track at the RSA Conference 2014, San Francisco, CA, USA,

February 25-28, 2014. Proceedings, 2014, pp. 227–250.

A. Biryukov, V. Velichkov, and Y. L. Corre, “Automatic search for

the best trails in ARX: application to block cipher speck,” in Fast

Software Encryption - 23rd International Conference, FSE 2016, Bochum,

Germany, March 20-23, 2016, Revised Selected Papers, 2016, pp. 289–

T. Cazenave, “Nested monte-carlo search,” in IJCAI 2009, Proceedings

of the 21st International Joint Conference on Artificial Intelligence,

Pasadena, California, USA, July 11-17, 2009, 2009, pp. 456–461.

M. Matsui, Ed., Fast Software Encryption, 8th International Workshop,

FSE 2001 Yokohama, Japan, April 2-4, 2001, Revised Papers, ser.

Lecture Notes in Computer Science, vol. 2355. Springer, 2002.

[Online]. Available: https://doi.org/10.1007/3-540-45473-X

D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den

Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot,

S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever,

T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis,

“Mastering the game of Go with deep neural networks and tree search,”

Nature, vol. 529, no. 7587, pp. 484–489, 2016.

Downloads

Published

2018-04-27

Issue

Section

Cryptography and Cybersecurity