Welcome to the resource topic for 2015/481
Title:
Advanced Differential Cryptanalysis of Reduced-Round SIMON64/128 Using Large-Round Statistical Distinguishers
Authors: Theodosis Mourouzis, Guangyan Song, Nicolas Courtois, Michalis Christofii
Abstract:Lightweight cryptography is a rapidly evolving area of research and it has great impact especially on the new computing environment called the Internet of Things (IoT) or the Smart Object networks (Holler et al., 2014), where lots of constrained devices are connected on the Internet and exchange information on a daily basis. Every year there are many new submissions of cryptographic primitives which are optimized towards both software and hardware implementation so that they can operate in devices which have limited resources of hardware and are subject to both power and energy consumption constraints. In 2013, two families of ultra-lightweight block ciphers were proposed, SIMON and SPECK, which come in a variety of block and key sizes and were designed to be optimized in hardware and software implementation respectively (Beaulieu et al., 2013). In this paper, we study the security of the 64-bit SIMON with 128-bit key against advanced forms of differential cryptanalysis using truncated differentials (Knudsen, 1995; Courtois et al., 2014a). We follow similar method as the one proposed in SECRYPT 2013 (Courtois and Mourouzis, 2013) in order to heuristically discover sets of differences that propagate with sufficiently good probability and allow us to combine them efficiently in order to construct large-round statistical distinguishers. We present a 22-round distinguisher which we use it in a depth-first key search approach to develop an attack against 24 and 26 rounds with complexity 2^{124.5} and 2^{126} SIMON encryptions respectively. Our methodology provides a framework for extending distinguishers to attacks to a larger number of rounds assuming truncated differential properties of relatively high probability were discovered.
ePrint: https://eprint.iacr.org/2015/481
See all topics related to this paper.
Feel free to post resources that are related to this paper below.
Example resources include: implementations, explanation materials, talks, slides, links to previous discussions on other websites.
For more information, see the rules for Resource Topics .