An Improved Distinguisher for Dragon.
Joo Yeon Cho, Josef Pieprzyk · QUT ePrints (Queensland University of Technology) · 2007
Abstract. Dragon stream cipher is one of the focus ciphers which have reached Phase 2 of the eSTREAM project. In this paper, we present a new method of building a linear distinguisher for Dragon. The distinguisher is constructed by exploiting the biases of two S-boxes and the modular addition which are basic components of the nonlinear function F. The bias of the distinguisher is estimated to be around 2 −75.32 which is better than the bias of the distinguisher presented by Englund and Maximov. We have shown that Dragon is distinguishable from a random cipher by using around 2 150.6 keystream words and 2 59 memory. In addition, we present a very efficient algorithm for computing the bias of linear approximation of modular addition.