Improving Key-Recovery in Linear Attacks: Application to 28-Round PRESENT

International audienceLinear cryptanalysis is one of the most important tools in usefor the security evaluation of symmetric primitives. Many improvementsand refinements have been published since its introduction, and manyapplications on different ciphers have been found. Among these upgrades,Collard et al. proposed in 2007 an acceleration of the key-recovery partof Algorithm 2 for last-round attacks based on the FFT.In this paper we present a generalized, matrix-based version of the pre-vious algorithm which easily allows us to take into consideration an ar-bitrary number of key-recovery rounds. We also provide efficient variantsthat exploit the key-schedule relations and that can be combined withmultiple linear attacks.Using our algorithms we provide some new cryptanalysis on PRESENT,including, to the best of our knowledge, the first attack on 28 rounds

Techniques améliorées pour la cryptanalyse des primitives symétriques

This thesis proposes improvements which can be applied to several techniques for the cryptanalysis of symmetric primitives. Special attention is given to linear cryptanalysis, for which a technique based on the fast Walsh transform was already known (Collard et al., ICISIC 2007). We introduce a generalised version of this attack, which allows us to apply it on key recovery attacks over multiple rounds, as well as to reduce the complexity of the problem using information extracted, for example, from the key schedule. We also propose a general technique for speeding key recovery attacks up which is based on the representation of Sboxes as binary decision trees. Finally, we showcase the construction of a linear approximation of the full version of the Gimli permutation using mixed-integer linear programming (MILP) optimisation.Dans cette thèse, on propose des améliorations qui peuvent être appliquées à plusieurs techniques de cryptanalyse de primitives symétriques. On dédie une attention spéciale à la cryptanalyse linéaire, pour laquelle une technique basée sur la transformée de Walsh rapide était déjà connue (Collard et al., ICISC 2007). On introduit une version généralisée de cette attaque, qui permet de l'appliquer pour la récupération de clé considerant plusieurs tours, ainsi que le réduction de la complexité du problème en utilisant par example des informations provénantes du key-schedule. On propose aussi une technique générale pour accélérer les attaques par récupération de clé qui est basée sur la représentation des boîtes S en tant que arbres binaires. Finalement, on montre comment on a obtenu une approximation linéaire sur la version complète de la permutation Gimli en utilisant l'optimisation par mixed-integer linear programming (MILP)

Multidimensional linear cryptanalysis

Linear cryptanalysis is an important tool for studying the security of symmetric ciphers. In 1993 Matsui proposed two algorithms, called Algorithm 1 and Algorithm 2, for recovering information about the secret key of a block cipher. The algorithms exploit a biased probabilistic relation between the input and output of the cipher. This relation is called the (one-dimensional) linear approximation of the cipher. Mathematically, the problem of key recovery is a binary hypothesis testing problem that can be solved with appropriate statistical tools. The same mathematical tools can be used for realising a distinguishing attack against a stream cipher. The distinguisher outputs whether the given sequence of keystream bits is derived from a cipher or a random source. Sometimes, it is even possible to recover a part of the initial state of the LFSR used in a key stream generator. Several authors considered using many one-dimensional linear approximations simultaneously in a key recovery attack and various solutions have been proposed. In this thesis a unified methodology for using multiple linear approximations in distinguishing and key recovery attacks is presented. This methodology, which we call multidimensional linear cryptanalysis, allows removing unnecessary and restrictive assumptions. We model the key recovery problems mathematically as hypothesis testing problems and show how to use standard statistical tools for solving them. We also show how the data complexity of linear cryptanalysis on stream ciphers and block ciphers can be reduced by using multiple approximations. We use well-known mathematical theory for comparing different statistical methods for solving the key recovery problems. We also test the theory in practice with reduced round Serpent. Based on our results, we give recommendations on how multidimensional linear cryptanalysis should be used

Improving the key recovery in Linear Cryptanalysis: An application to PRESENT

International audienceLinear cryptanalysis is widely known as one of the fundamental tools for the crypanalysis of block ciphers. Over the decades following its first introduction by Matsui in [Ma94a], many different extensions and improvements have been proposed. One of them is [CSQ07], where Collard et al. use the Fast Fourier Transform (FFT) to accelerate the parity computations which are required to perform a linear key recovery attack. Modified versions of this technique have been introduced in order to adapt it to the requirements of several dedicated linear attacks. This work provides a model which extends and improves these different contributions and allows for a general expression of the time and memory complexities that are achieved. The potential of this general approach will then be illustrated with new linear attacks on reduced-round PRESENT, which is a very popular and widely studied lightweight cryptography standard. In particular, we show an attack on 26 or 27-round PRESENT-80 which has better time and data complexity than any previously known attacks, as well as the first attack on 28-round PRESENT-128

Joint Data and Key Distribution of Simple, Multiple, and Multidimensional Linear Cryptanalysis Test Statistic and Its Impact to Data Complexity

The power of a statistical attack is inversely proportional to the number of plaintexts needed to recover information on the encryption key. By analyzing the distribution of the random variables involved in the attack, cryptographers aim to provide a good estimate of the data complexity of the attack. In this paper, we analyze the hypotheses made in simple, multiple, and multidimensional linear attacks that use either non-zero or zero correlations, and provide more accurate estimates of the data complexity of these attacks. This is achieved by taking, for the first time, into consideration the key variance of the statistic for both the right and wrong keys. For the family of linear attacks considered in this paper, we differentiate between the attacks which are performed in the known-plaintext and those in the distinct-known-plaintext model

Conditional Linear Cryptanalysis – Cryptanalysis of DES with Less Than 242 Complexity

In this paper we introduce a new extension of linear cryptanalysis that may reduce the complexity of attacks by conditioning linear approximations on other linear approximations. We show that the bias of some linear approximations may increase under such conditions, so that after discarding the known plaintexts that do not satisfy the conditions, the bias of the remaining known plaintexts increases. We show that this extension can lead to improvements of attacks, which may require fewer known plaintexts and time of analysis. We present several types of such conditions, including one that is especially useful for the analysis of Feistel ciphers. We exemplify the usage of such conditions for attacks by a careful application of our extension to Matsui’s attack on the full 16-round DES, which succeeds to reduce the complexity of the best attack on DES to less than 242. We programmed a test implementation of our attack and verified our claimed results with a large number of runs. We also introduce a new type of approximations, to which we call scattered approximations, and discuss its applications

Multivariate Profiling of Hulls for Linear Cryptanalysis

Extensions of linear cryptanalysis making use of multiple approximations, such as multiple and multidimensional linear cryptanalysis, are an important tool in symmetric-key cryptanalysis, among others being responsible for the best known attacks on ciphers such as Serpent and present. At CRYPTO 2015, Huang et al. provided a refined analysis of the key-dependent capacity leading to a refined key equivalence hypothesis, however at the cost of additional assumptions. Their analysis was extended by Blondeau and Nyberg to also cover an updated wrong key randomization hypothesis, using similar assumptions. However, a recent result by Nyberg shows the equivalence of linear dependence and statistical dependence of linear approximations, which essentially invalidates a crucial assumption on which all these multidimensional models are based. In this paper, we develop a model for linear cryptanalysis using multiple linearly independent approximations which takes key-dependence into account and complies with Nyberg’s result. Our model considers an arbitrary multivariate joint distribution of the correlations, and in particular avoids any assumptions regarding normality. The analysis of this distribution is then tailored to concrete ciphers in a practically feasible way by combining a signal/noise decomposition approach for the linear hulls with a profiling of the actual multivariate distribution of the signal correlations for a large number of keys, thereby entirely avoiding assumptions regarding the shape of this distribution. As an application of our model, we provide an attack on 26 rounds of present which is faster and requires less data than previous attacks, while using more realistic assumptions and far fewer approximations. We successfully extend the attack to present the first 27-round attack which takes key-dependence into account

Analysis and resynthesis of polyphonic music

This thesis examines applications of Digital Signal Processing to the analysis, transformation, and resynthesis of musical audio. First I give an overview of the human perception of music. I then examine in detail the requirements for a system that can analyse, transcribe, process, and resynthesise monaural polyphonic music. I then describe and compare the possible hardware and software platforms. After this I describe a prototype hybrid system that attempts to carry out these tasks using a method based on additive synthesis. Next I present results from its application to a variety of musical examples, and critically assess its performance and limitations. I then address these issues in the design of a second system based on Gabor wavelets. I conclude by summarising the research and outlining suggestions for future developments

Computer Models for Musical Instrument Identification

PhDA particular aspect in the perception of sound is concerned with what is commonly termed as texture or timbre. From a perceptual perspective, timbre is what allows us to distinguish sounds that have similar pitch and loudness. Indeed most people are able to discern a piano tone from a violin tone or able to distinguish different voices or singers. This thesis deals with timbre modelling. Specifically, the formant theory of timbre is the main theme throughout. This theory states that acoustic musical instrument sounds can be characterised by their formant structures. Following this principle, the central point of our approach is to propose a computer implementation for building musical instrument identification and classification systems. Although the main thrust of this thesis is to propose a coherent and unified approach to the musical instrument identification problem, it is oriented towards the development of algorithms that can be used in Music Information Retrieval (MIR) frameworks. Drawing on research in speech processing, a complete supervised system taking into account both physical and perceptual aspects of timbre is described. The approach is composed of three distinct processing layers. Parametric models that allow us to represent signals through mid-level physical and perceptual representations are considered. Next, the use of the Line Spectrum Frequencies as spectral envelope and formant descriptors is emphasised. Finally, the use of generative and discriminative techniques for building instrument and database models is investigated. Our system is evaluated under realistic recording conditions using databases of isolated notes and melodic phrases

General Statistical Design of an Experimental Problem for Harmonics

Four years ago, the Michelin Tire Corporation proposed a problem on experimental design, to improve the manufacturing process for their tires. The idea is basically to determine the effects of placements for various layers built up in the construction of a tire, to allow the design of a smooth tire with a smooth ride. A highly success solution was developed, and it has been reported that this method introduced savings of over half a million dollars in their test processes. This year, Michelin returned to the workshop with an extension to the original problem, to address specific refinements in the testing method. This report summarizes the work completed in course of the five day workshop. It was clear early in the workshop that this problem could be handled quickly by reviewing the analysis which was done in 2000, and extending those ideas to the new problems at hand. We reviewed the required Fourier techniques to describe the harmonic problem, and statistical techniques to deal with the linear model that described how to accurately measure quantities that come from real experimental measurements. The “prime method” and “good lattice points method” were reviewed and re-analysed so we could understand (and prove) why they work so well. We then looked at extending these methods and successfully found solutions to problem 1) and 2) posed by Michelin. Matlab code was written to test and verify the algorithms developed. We have some ideas on problems 3) and 4), which are also described