A Comparison of Time-Memory Trade-Off Attacks on Stream Ciphers

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The Design Space of Lightweight Cryptography

International audienceFor constrained devices, standard cryptographic algorithms can be too big, too slow or too energy-consuming. The area of lightweight cryptography studies new algorithms to overcome these problems. In this paper, we will focus on symmetric-key encryption, authentication and hashing. Instead of providing a full overview of this area of research, we will highlight three interesting topics. Firstly, we will explore the generic security of lightweight constructions. In particular, we will discuss considerations for key, block and tag sizes, and explore the topic of instantiating a pseudorandom permutation (PRP) with a non-ideal block cipher construction. This is inspired by the increasing prevalence of lightweight designs that are not secure against related-key attacks, such as PRINCE, PRIDE or Chaskey. Secondly, we explore the efficiency of cryptographic primitives. In particular, we investigate the impact on efficiency when the input size of a primitive doubles. Lastly, we provide some considerations for cryptographic design. We observe that applications do not always use cryptographic algorithms as they were intended, which negatively impacts the security and/or efficiency of the resulting implementations

Comparison of Cryptanalytic Time Memory Tradeoff Algorithms with Focus on Some Rainbow Variants

학위논문 (박사)-- 서울대학교 대학원 : 수리과학부, 2016. 2. 홍진.Cryptanalytic time memory tradeoff algorithms are tools for inverting one-way functions, and they are used to recover passwords from unsalted password hashes. There are many publicly known tradeoff algorithms, and the rainbow tradeoff algorithm, which is widely believed to be the best tradeoff algorithm, at least among implementers, has been the most popular method. In this thesis, we provide accurate complexity analyses of the thick rainbow tradeoff algorithm and the non-perfect and perfect table fuzzy rainbow tradeoff algorithms. These are algorithms that have not yet received much attention. Our analyses show that, when the pre-computation cost and the online execution efficiency are both taken into consideration, the perfect table fuzzy rainbow tradeoff can be seen as performing the best among the three algorithms considered and actually even better than the original rainbow tradeoff. The computational complexities for some time memory data tradeoff methods are also analyzed. The multi-target tradeoffs that we cover are the classical Hellman, distinguished point, and fuzzy rainbow methods, both in their non-perfect and perfect table versions for the latter two methods. We find that their execution complexities are no different from the complexities of the corresponding single-target algorithms executed under certain matching parameters. As in the single-target case, we conclude that the perfect table fuzzy rainbow tradeoff algorithm is the most preferable among the multi-target tradeoff algorithms we have considered.Chapter 1 Introduction 1 Chapter 2 Preliminaries 5 2.1 Previous Results of Major Algorithms 7 2.1.1 Hellman Tradeoff 7 2.1.2 DP Tradeoff 8 2.1.3 Rainbow Tradeoff 10 2.2 Some Rainbow Variants 11 2.2.1 Thick Rainbow Tradeoff 12 2.2.2 Non-Perfect Table Fuzzy Rainbow Tradeoff 13 2.2.3 Perfect Table Fuzzy Rainbow Tradeoff 15 Chapter 3 Analyses of the Three Rainbow Variants 18 3.1 Thick Rainbow Tradeoff 18 3.1.1 Probability of Success 18 3.1.2 Online Complexity 21 3.2 Non-Perfect Table Fuzzy Rainbow Tradeoff 25 3.2.1 Probability of Success 25 3.2.2 Online Complexity 31 3.3 Perfect Table Fuzzy Rainbow Tradeoff 37 3.3.1 Probability of Success 37 3.3.2 Online Complexity 41 Chapter 4 Storage Optimization 49 4.1 The Degree of Ending Point Truncation 50 4.1.1 Thick Rainbow Tradeoff 50 4.1.2 Non-Perfect Table Fuzzy Rainbow Tradeoff 52 4.1.3 Perfect Table Fuzzy Rainbow Tradeoff 54 Chapter 5 Comparison of Algorithms 56 5.1 Adjustment Factors for Tradeoff Coefficients 56 5.2 Some Observations concerning Fuzzy Rainbow Tradeoffs 58 5.3 Comparison 63 Chapter 6 Time Memory Data Tradeoff Algorithms 67 6.1 Algorithms 67 6.2 Analysis 69 Chapter 7 Experiments 72 7.1 Thick Rainbow Tradeoff 72 7.2 Non-Perfect Table Fuzzy Rainbow Tradeoff 74 7.3 Perfect Table Fuzzy Rainbow Tradeoff 78 7.4 Time Memory Data Tradeoff Algorithms 84 Chapter 8 Conclusion 86 Abstract (in Korean) 91Docto