Welcome to the resource topic for 2018/161
Title:
Boomerang Connectivity Table: A New Cryptanalysis Tool
Authors: Carlos Cid, Tao Huang, Thomas Peyrin, Yu Sasaki, Ling Song
Abstract:A boomerang attack is a cryptanalysis framework that regards a block cipher E as the composition of two sub-ciphers E_1\circ E_0 and builds a particular characteristic for E with probability p^2q^2 by combining differential characteristics for E_0 and E_1 with probability p and q, respectively. Crucially the validity of this figure is under the assumption that the characteristics for E_0 and E_1 can be chosen independently. Indeed, Murphy has shown that independently chosen characteristics may turn out to be incompatible. On the other hand, several researchers observed that the probability can be improved to p or q around the boundary between E_0 and E_1 by considering a positive dependency of the two characteristics, e.g.~the ladder switch and S-box switch by Biryukov and Khovratovich. This phenomenon was later formalised by Dunkelman et al.~as a sandwich attack that regards E as E_1\circ E_m \circ E_0, where E_m satisfies some differential propagation among four texts with probability r, and the entire probability is p^2q^2r. In this paper, we revisit the issue of dependency of two characteristics in E_m, and propose a new tool called Boomerang Connectivity Table (BCT), which evaluates r in a systematic and easy-to-understand way when E_m is composed of a single S-box layer. With the BCT, previous observations on the S-box including the incompatibility, the ladder switch and the S-box switch are represented in a unified manner. Moreover, the BCT can detect a new switching effect, which shows that the probability around the boundary may be even higher than p or q. To illustrate the power of the BCT-based analysis, we improve boomerang attacks against Deoxys-BC, and disclose the mechanism behind an unsolved probability amplification for generating a quartet in SKINNY. Lastly, we discuss the issue of searching for S-boxes having good BCT and extending the analysis to modular addition.
ePrint: https://eprint.iacr.org/2018/161
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