Author: Daniel Neuenschwander
Publisher: Springer Science & Business Media
Published: 2004-04-30
Total Pages: 155
ISBN-13: 3540220011
DOWNLOAD EBOOK →Cryptology nowadays is one of the most important areas of applied mathematics, building on deep results and methods from various areas of mathematics. This text is devoted to the study of stochastic aspects of cryptology. Besides classical topics from cryptology, the author presents chapters on probabilistic prime number tests, factorization with quantum computers, random-number generators, pseudo-random-number generators, information theory, and the birthday paradox and meet-in-the-middle attack. In the light of the vast literature on stochastic results relevant for cryptology, this book is intended as an invitation and introduction for students, researchers, and practitioners to probabilistic and statistical issues in cryptology.
Author: Daniel Neuenschwander
Publisher:
Published: 2014-01-15
Total Pages: 172
ISBN-13: 9783662203309
DOWNLOAD EBOOK →Author: George Lasry
Publisher: kassel university press GmbH
Published: 2018
Total Pages: 249
ISBN-13: 3737604584
DOWNLOAD EBOOK →Cryptography, the art and science of creating secret codes, and cryptanalysis, the art and science of breaking secret codes, underwent a similar and parallel course during history. Both fields evolved from manual encryption methods and manual codebreaking techniques, to cipher machines and codebreaking machines in the first half of the 20th century, and finally to computerbased encryption and cryptanalysis from the second half of the 20th century. However, despite the advent of modern computing technology, some of the more challenging classical cipher systems and machines have not yet been successfully cryptanalyzed. For others, cryptanalytic methods exist, but only for special and advantageous cases, such as when large amounts of ciphertext are available. Starting from the 1990s, local search metaheuristics such as hill climbing, genetic algorithms, and simulated annealing have been employed, and in some cases, successfully, for the cryptanalysis of several classical ciphers. In most cases, however, results were mixed, and the application of such methods rather limited in their scope and performance. In this work, a robust framework and methodology for the cryptanalysis of classical ciphers using local search metaheuristics, mainly hill climbing and simulated annealing, is described. In an extensive set of case studies conducted as part of this research, this new methodology has been validated and demonstrated as highly effective for the cryptanalysis of several challenging cipher systems and machines, which could not be effectively cryptanalyzed before, and with drastic improvements compared to previously published methods. This work also led to the decipherment of original encrypted messages from WWI, and to the solution, for the first time, of several public cryptographic challenges.
Author: Wei Dai
Publisher:
Published: 2016
Total Pages: 63
ISBN-13: 9781369340631
DOWNLOAD EBOOK →Cryptographic assumptions and security goals are fundamentally distributional. As a result, statistical techniques are ubiquitous in cryptographic constructions and proofs. In this thesis, we build upon existing techniques and seek to improve both theoretical and practical constructions in three fundamental primitives in cryptography: blockciphers, hash functions, and encryption schemes. First, we present a tighter hybrid argument via collision probability that is more general than previously known, allowing applications to blockciphers. We then use our result to improve the bound of the Swap-or-Not cipher. We also develop a new blockcipher composition theorem that is both class and security amplifying. Second, we prove a variant of Leftover Hash Lemma for joint leakage, inspired by the Universal Computational Extractor (UCE) assumption. We then apply this technique to construct various standard-model UCE- secure hash functions. Third, we survey existing "lossy primitives" in cryptography, in particular Lossy Trapdoor Functions (LTDF) and Lossy Encryptions (LE); we pro- pose a generalized primitive called Lossy Deterministic Encryption (LDE). We show that LDE is equivalent to LTDFs. This is in contrast with the block-box separation of trapdoor functions and public-key encryption schemes in the computational case. One common theme in our methods is the focus on statistical techniques. Another theme is that the results obtained are in contrast with their computational counterparts--the corresponding computational results are implausible or are know to be false.