8 research outputs found

    Improved Meet-in-the-Middle Attacks on Round-Reduced Crypton-256

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    The meet-in-the-middle (MITM) attack has prove to be efficient in analyzing the AES block cipher. Its efficiency has been increasing with the introduction of various techniques such as differential enumeration, key-dependent sieve, super-box etc. The recent MITM attack given by Li and Jin has successfully mounted to 10-round AES-256. Crypton is an AES-like block cipher. In this paper, we apply the MITM method to the cryptanalysis of Crypton-256. Following Li and Jin\u27s idea, we give the first 6-round distinguisher for Crypton. Based on the distinguisher as well as the properties of Crypton\u27s simple key schedule, we successfully launch MITM attacks on Crypton-256 reduced to 9 and 10 rounds. For 9-round Crypton-256, our MITM attack can recover the 256-bit key with a time complexity 2173.052^{173.05}, a memory complexity 2241.172^{241.17}. For the 10-round version, we give two MITM attacks. The basic attack requires a time complexity 2240.012^{240.01} and memory complexity 2241.592^{241.59}. The time/memory complexity of the advanced MITM attack on 10-round Crypton is 2245.05/2209.592^{245.05}/2^{209.59}. Our MITM attacks share the same data complexity 21132^{113} and their error rates are negligible

    KLEIN: A New Family of Lightweight Block Ciphers

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    Resource-efficient cryptographic primitives become fundamental for realizing both security and efficiency in embedded systems like RFID tags and sensor nodes. Among those primitives, lightweight block cipher plays a major role as a building block for security protocols. In this paper, we describe a new family of lightweight block ciphers named KLEIN, which is designed for resource-constrained devices such as wireless sensors and RFID tags. Compared to the related proposals, KLEIN has advantage in the software performance on legacy sensor platforms, while in the same time its hardware implementation can also be compact

    How Far Can We Go Beyond Linear Cryptanalysis?

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    Several generalizations of linear cryptanalysis have been proposed in the past, as well as very similar attacks in a statistical point of view. In this paper, we define a rigorous general statistical framework which allows to interpret most of these attacks in a simple and unified way. Then, we explicitely construct optimal distinguishers, we evaluate their performance, and we prove that a block cipher immune to classical linear cryptanalysis possesses some resistance to a wide class of generalized versions, but not all. Finally, we derive tools which are necessary to set up more elaborate extensions of linear cryptanalysis, and to generalize the notions of bias, characteristic, and piling-up lemma

    A Salad of Block Ciphers

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    This book is a survey on the state of the art in block cipher design and analysis. It is work in progress, and it has been for the good part of the last three years -- sadly, for various reasons no significant change has been made during the last twelve months. However, it is also in a self-contained, useable, and relatively polished state, and for this reason I have decided to release this \textit{snapshot} onto the public as a service to the cryptographic community, both in order to obtain feedback, and also as a means to give something back to the community from which I have learned much. At some point I will produce a final version -- whatever being a ``final version\u27\u27 means in the constantly evolving field of block cipher design -- and I will publish it. In the meantime I hope the material contained here will be useful to other people

    HUC-HISF: A Hybrid Intelligent Security Framework for Human-centric Ubiquitous Computing

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    制度:新 ; 報告番号:乙2336号 ; 学位の種類:博士(人間科学) ; 授与年月日:2012/1/18 ; 早大学位記番号:新584

    Quantitative security of block ciphers:designs and cryptanalysis tools

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    Block ciphers probably figure in the list of the most important cryptographic primitives. Although they are used for many different purposes, their essential goal is to ensure confidentiality. This thesis is concerned by their quantitative security, that is, by measurable attributes that reflect their ability to guarantee this confidentiality. The first part of this thesis deals with well know results. Starting with Shannon's Theory of Secrecy, we move to practical implications for block ciphers, recall the main schemes on which nowadays block ciphers are based, and introduce the Luby-Rackoff security model. We describe distinguishing attacks and key-recovery attacks against block ciphers and show how to turn the firsts into the seconds. As an illustration, we recall linear cryptanalysis which is a classical example of statistical cryptanalysis. In the second part, we consider the (in)security of block ciphers against statistical cryptanalytic attacks and develop some tools to perform optimal attacks and quantify their efficiency. We start with a simple setting in which the adversary has to distinguish between two sources of randomness and show how an optimal strategy can be derived in certain cases. We proceed with the practical situation where the cardinality of the sample space is too large for the optimal strategy to be implemented and show how this naturally leads to the concept of projection-based distinguishers, which reduce the sample space by compressing the samples. Within this setting, we re-consider the particular case of linear distinguishers and generalize them to sets of arbitrary cardinality. We show how these distinguishers between random sources can be turned into distinguishers between random oracles (or block ciphers) and how, in this setting, one can generalize linear cryptanalysis to Abelian groups. As a proof of concept, we show how to break the block cipher TOY100, introduce the block cipher DEAN which encrypts blocks of decimal digits, and apply the theory to the SAFER block cipher family. In the last part of this thesis, we introduce two new constructions. We start by recalling some essential notions about provable security for block ciphers and about Serge Vaudenay's Decorrelation Theory, and introduce new simple modules for which we prove essential properties that we will later use in our designs. We then present the block cipher C and prove that it is immune against a wide range of cryptanalytic attacks. In particular, we compute the exact advantage of the best distinguisher limited to two plaintext/ciphertext samples between C and the perfect cipher and use it to compute the exact value of the maximum expected linear probability (resp. differential probability) of C which is known to be inversely proportional to the number of samples required by the best possible linear (resp. differential) attack. We then introduce KFC a block cipher which builds upon the same foundations as C but for which we can prove results for higher order adversaries. We conclude both discussions about C and KFC by implementation considerations
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