In this thesis we deal with the Boolean functions with particular difference distribution vectors. Besides the main properties, we especially focus on strict avalanche criterion for cryptographic aspects. Not only we deal with known methods we also demonstrate some new methods for counting and constructing such functions. Furthermore, performing some statistical tests, we observed a number of interesting properties.

Graph communication protocols are a generalization of classical communi- cation protocols to the case when the underlying graph is a directed acyclic graph. Motivated by potential applications in proof complexity, we study variants of graph communication protocols and relations between them. The main result is a comparison of the strength of two types of protocols, protocols with equality and protocols with a conjunction of a constant num- ber of inequalities. We prove that protocols of the first type are at least as strong as protocols of the second type in the following sense: For a Boolean function f, if there is a protocol with a conjunction of a constant number of inequalities of polynomial size solving f, then there is a protocol with equality of polynomial size solving f. We also introduce two new types of graph communication protocols, protocols with disjointness and protocols with non-disjointness, and prove that the first type is at least as strong as the previously considered protocols and that the second type is too strong to be useful for applications.

AN ABSTRACT OF THE DISSERTATION OF PRAGYAN P. MOHANTY, for the Doctor of Philosophy degree in ELECTRICAL AND COMPUTER ENGINEERING, presented on June 11, 2015, at Southern Illinois University Carbondale. TITLE: FUNCTION-BASED ALGORITHMS FOR BIOLOGICAL SEQUENCES MAJOR PROFESSOR: Dr. Spyros Tragoudas Two problems at two different abstraction levels of computational biology are studied. At the molecular level, efficient pattern matching algorithms in DNA sequences are presented. For gene order data, an efficient data structure is presented capable of storing all gene re-orderings in a systematic manner. A common characteristic of presented methods is the use of binary decision diagrams that store and manipulate binary functions. Searching for a particular pattern in a very large DNA database, is a fundamental and essential component in computational biology. In the biological world, pattern matching is required for finding repeats in a particular DNA sequence, finding motif and aligning sequences etc. Due to immense amount and continuous increase of biological data, the searching process requires very fast algorithms. This also requires encoding schemes for efficient storage of these search processes to operate on. Due to continuous progress in genome sequencing, genome rearrangements and construction of evolutionary genome graphs, which represent the relationships between genomes, become challenging tasks. Previous approaches are largely based on distance measure so that relationship between more phylogenetic species can be established with some specifically required rearrangement operations and hence within certain computational time. However because of the large volume of the available data, storage space and construction time for this evolutionary graph is still a problem. In addition, it is important to keep track of all possible rearrangement operations for a particular genome as biological processes are uncertain. This study presents a binary function-based tool set for efficient DNA sequence storage. A novel scalable method is also developed for fast offline pattern searches in large DNA sequences. This study also presents a method which efficiently stores all the gene sequences associated with all possible genome rearrangements such as transpositions and construct the evolutionary genome structure much faster for multiple species. The developed methods benefit from the use of Boolean functions; their compact storage using canonical data structure and the existence of built-in operators for these data structures. The time complexities depend on the size of the data structures used for storing the functions that represent the DNA sequences and/or gene sequences. It is shown that the presented approaches exhibit sub linear time complexity to the sequence size. The number of nodes present in the DNA data structure, string search time on these data structures, depths of the genome graph structure, and the time of the rearrangement operations are reported. Experiments on DNA sequences from the NCBI database are conducted for DNA sequence storage and search process. Experiments on large gene order data sets such as: human mitochondrial data and plant chloroplast data are conducted and depth of this structure was studied for evolutionary processes on gene sequences. The results show that the developed approaches are scalable.

L’analyse de groupes de données binaires est aujourd’hui un défi au vu des quantités de données collectées. Elle peut être réalisée par des approches logiques. Ces approches identifient dessous-ensembles d’attributs booléens pertinents pour caractériser les observations d’un groupe et peuvent aider l’utilisateur à mieux comprendre les propriétés de ce groupe.Cette thèse présente une approche pour caractériser des groupes de données binaires en identifiant un sous-ensemble minimal d’attributs permettant de distinguer les données de différents groupes.Nous avons défini avec précision le problème de la caractérisation multiple et proposé de nouveaux algorithmes qui peuvent être utilisés pour résoudre ses différentes variantes. Notre approche de caractérisation de données peut être étendue à la recherche de patterns (motifs) dans le cadre de l’analyse logique de données. Un pattern peut être considéré comme une explication partielle des observations positives pouvant être utilisées par les praticiens, par exemple à des fins de diagnostic. De nombreux patterns existent et plusieurs critères de préférence peuvent être ajoutés pour se concentrer sur des ensembles plus restreints (prime patterns,strong patterns,. . .). Nous proposons donc une comparaison entre ces deux méthodologies ainsi que des algorithmes pour générer des patterns. Un autre objectif est d’étudier les propriétés des solutions calculées en fonction des propriétés topologiques des instances. Des expériences sont menées sur de véritables ensembles de données biologiques. / Analysis of groups of binary data is now a challenge given the amount of collected data. It can be achieved by logical based approaches. These approaches identify subsets of relevant Boolean attributes to characterize the observations of a group and may help the user to better understand the properties of this group. This thesis presents an approach for characterizing groups of binary data by identifying a minimal subset of attributes that allows to distinguish data from different groups. We have precisely defined the multiple characterization problem and proposed new algorithms that can be used to solve its different variants. Our data characterization approach can be extended to search for patterns in the framework of logical analysis of data. A pattern can be considered as a partial explanation of the positive observations that can be used by practitioners, for instance for diagnosis purposes. Many patterns may exist and several preference criteria can be added in order to focus on more restricted sets of patterns (prime patterns, strong patterns, . . . ). We propose a comparison between these two methodologies as well as algorithms for generating patterns. The purpose is also to precisely study the properties of the solutions that are computed with regards to the topological properties of the instances. Experiments are thus conducted on real biological data.

The open problem in knowledge compilation of whether the language PI is at least as succinct as MODS is answered in the negative. For this purpose a class of Boolean functions with a number of prime implicants that is superpolynomial in their number of false points is constructed. A lower bound (proving that PI is not at least as succinct as MODS), an upper bound (proving that the counterexample cannot yield an exponential separation of PI and MODS) and the precise number of the prime implicants of these functions is computed. Powered by TCPDF (www.tcpdf.org)

Le chiffrement complètement homomorphe est une classe de chiffrement permettant de calculer n’importe quelle fonction sur des données chiffrées et de produire une version chiffrée du résultat. Il permet de déléguer des données à un cloud de façon sécurisée, faire effectuer des calculs, tout en gardant le caractère privé de ces données. Cependant, l’innéficacité actuelle des schémas de chiffrement complètement homomorphes, et leur inadéquation au contexte de délégation de calculs, rend son usage seul insuffisant pour cette application. Ces deux problèmes peuvent être résolus, en utilisant ce chiffrement dans un cadre plus large, en le combinant avec un schéma de chiffrement symétrique. Cette combinaison donne naissance au chiffrement complètement homomorphe hybride, conçu dans le but d’une délégation de calculs efficace, garantissant des notions de sécurité et de vie privée. Dans cette thèse, nous étudions le chiffrement complètement homomorphe hybride et ses composantes, à travers la conception de primitives cryptographiques symétriques rendant efficace cette construction hybride. En examinant les schémas de chiffrement complètement homomorphes, nous developpons des outils pour utiliser efficacement leurs propriétés homomorphiques dans un cadre plus complexe. En analysant différents schémas symétriques, et leurs composantes, nous déterminons de bons candidats pour le contexte hybride. En étudiant la sécurité des constructions optimisant l’évaluation homomorphique, nous contribuons au domaine des fonctions booléennes utilisées en cryptologie. Plus particulièrement, nous introduisons une nouvelle famille de schémas de chiffrement symétriques, avec une nouvelle construction, adaptée au contexte hybride. Ensuite, nous nous intéressons à son comportement homomorphique, et nous étudions la sécurité de cette construction. Finalement, les particularités de cette famille de schémas de chiffrement motivant des cryptanalyses spécifiques, nous développons et analysons de nouveaux critères cryptographiques booléens. / Fully homomorphic encryption, firstly built in 2009, is a very powerful kind of encryption, allowing to compute any function on encrypted data, and to get an encrypted version of the result. Such encryption enables to securely delegate data to a cloud, ask for computations, recover the result, while keeping private the data during the whole process. However, today’s inefficiency of fully homomorphic encryption, and its inadequateness to the outsourcing computation context, makes its use alone insufficient for this application. Both of these issues can be circumvented, using fully homomorphic encryption in a larger framework, by combining it with a symmetric encryption scheme. This combination gives a hybrid fully homomorphic framework, designed towards efficient outsourcing computation, providing both security and privacy. In this thesis, we contribute to the study of hybridfully homomorphic framework, through the analysis, and the design of symmetric primitives making efficient this hybrid construction. Through the examination of fully homomorphic encryption schemes, we develop tools to efficiently use the homomorphic properties in a more complex framework. By investigating various symmetric encryption schemes, and buildingblocks up to the circuit level, we determine good candidates for a hybrid context. Through evaluating the security of constructions optimizing the homomorphic evaluation, we contribute to a wide study within the cryptographic Boolean functions area. More particularly, we introduce a new family of symmetric encryption schemes, with a new design, adapted to the hybrid fully homomorphic framework. We then investigate its behavior relatively to homomorphic evaluation, and we address the security of such design. Finally, particularities of this family of ciphers motivate specific cryptanalyses, therefore we develop and analyze new cryptographic Boolean criteria.

Efficient manipulation of Boolean functions is an important component of many computer-aided design task. As a data structure for representing and manipulating Boolean functions, Binary Decision Diagrams are commonly used. These diagrams are commonly used in many fields such as model checking, system verification, circuit design, etc. In this thesis we describe these diagrams and there are present their modifications. Furthermore, this paper present and describes techniques for effective handling and representation of binary decision diagrams. This thesis describes the design and implementation of library that will work with these diagrams. It is further discussed how the developed library can be used within the library VATA for manipulating tree automata. Finally, the library was compared with well known and heavily optimized library CUDD, which is public and with library CacBDD. The experimental results showed that the performance of the proposed library is quite close to that of CUDD a CacBDD (has comparable and mostly even slightly better performance).

Le but de cette thèse est l'étude des Automates Cellulaires (AC) dans la perspective des fonctions booléennes et des dessins combinatoires. Au-delà de son intérêt théorique, cette recherche est motivée par ses applications à la cryptographie, puisque les fonctions booléennes et les dessins combinatoires sont utilisés pour construire des générateurs de nombres pseudo aléatoires (Pseudorandom Number Generators, PRNG) et des schémas de partage de secret (Secret Sharing Schemes, SSS). Les résultats présentés dans la thèse ont été développés sur trois lignes de recherche, organisées comme suit. La première ligne porte sur l'utilisation des algorithmes d'optimisation heuristique pour chercher des fonctions booléennes ayant des bonnes propriétés cryptographiques, à utiliser comme des règles locales dans des PRNG basés sur les AC. La motivation principale est l'amélioration du générateur de Wolfram basé sur la règle 30, qui a été montré être vulnérable vis à vis de deux attaques cryptanalytiques. La deuxième ligne s'occupe des fonctions booléennes vectorielles engendrées par les règles globales des AC. La première contribution considère la période des pré-images des configurations spatialement périodiques dans les AC surjectifs, et l'analyse des propriétés cryptographiques des règles globales des AC. La troisième ligne se concentre sur les dessins combinatoires engendrés par les AC, en considérant les Carrés Latins Orthogonaux (Orthogonal Latin Squares, OLS), qui sont équivalents aux SSS. En particulier, on donne une caractérisation algébrique des OLS engendrés par les AC linéaires, et on utilise des algorithmes heuristiques pour construire des OLS basés sur des AC non linéaires. / The goal of this thesis is the investigation of Cellular Automata (CA) from the perspective of Boolean functions and combinatorial designs. Beside its theoretical interest, this research finds its motivation in cryptography, since Boolean functions and combinatorial designs are used to construct Pseudorandom Number Generators (PRNG) and Secret Sharing Schemes (SSS). The results presented in the thesis are developed along three research lines, organized as follows. The first line considers the use of heuristic optimization algorithms to search for Boolean functions with good cryptographic properties, to be used as local rules in CA-based PRNG. The main motivation is to improve Wolfram's generator based on rule 30, which has been shown to be vulnerable against two cryptanalytic attacks. The second line deals with vectorial Boolean functions induced by CA global rules. The first contribution considers the period of preimages of spatially periodic configurations in surjective CA, and analyze the cryptographic properties of CA global rules. The third line focuses on the combinatorial designs generated by CA, specifically considering Orthogonal Latin Squares (OLS), which are equivalent to SSS. In particular, an algebraic characterization of OLS generated by linear CA is given, and heuristic algorithms are used to build OLS based on nonlinear CA.

Este trabalho apresenta a composição funcional (CF) como um novo paradigma para realização da síntese lógica de blocos combinacionais. CF usa uma abordagem ascendente para sintetizar funções Booleanas, sendo capaz de avaliar os custos das funções intermediárias e explorando dessa forma um grande número de combinações diferentes de funções candidatas. Há vantagens interessantes quando comparado à abordagem descendente da decomposição funcional. CF apresenta grande flexibilidade para criar algoritmos com resultados ótimos ou subótimos para diferentes aplicações. A estratégia proposta apresenta bons resultados para síntese de funções Booleanas visando diferentes tecnologias. CF é baseado nos seguintes princípios: (1) representação de funções lógicas como um par ligado com representações funcional e estrutural; (2) o algoritmo começa de um conjunto de funções iniciais; (3) funções mais simples são associadas para criar funções mais complexas; (4) existe uma ordem parcial que permite o uso da programação dinâmica; (5) um conjunto de funções permitidas pode ser mantido para reduzir o tempo de execução/consumo de memória. Este trabalho apresenta algoritmos de composição funcional para fatoração Booleana, incluindo fatoração ótima, fatoração considerando o operador OU-exclusivo, computação de cadeias mínimas de decisão e síntese de funções considerando somente portas lógicas majoritárias e inversores. / This work presents functional composition (FC) as a new paradigm for combinational logic synthesis. FC is a bottom-up approach to synthesize Boolean functions, being able to evaluate the cost of intermediate sub-functions, exploring a larger number of different candidate combinations. These are interesting advantages when compared to the top-down behavior of functional decomposition. FC presents great flexibility to implement algorithms with optimal or suboptimal results for different applications. The proposed strategy presents good results for the synthesis of Boolean functions targeting different technologies. FC is based on the following principles: (1) the representation of logic functions is done by a bonded pair of functional and structural representations; (2) the algorithm starts from a set of initial functions; (3) simpler functions are associated to create more complex ones; (4) there is a partial order, enabling dynamic programming; (5) a set of allowed functions can be used in order to reduce execution time/memory consumption. This work presents functional composition algorithms for Boolean factoring, including optimal factoring, Boolean factoring considering the exclusive-OR operator, minimum decision chain computation and synthesis of functions considering only majority and inverter logic gates.

Vectorial Boolean functions are used as S-boxes in cryptosystems. To design inequivalent vectorial Boolean functions resistant to known attacks is one of the challenges in cryptography. Verifying whether two vectorial Boolean functions are equivalent or not is the final step in this challenge. Hence, finding a fast technique for determining whether two given vectorial Boolean functions are equivalent is an important problem. A special class of the equivalence called restricted extended affine (REA) equivalence is studied in this thesis. We study the verification complexity of REA-equivalence of two vectorial Boolean functions for some types, namely types I to VI. We first review the verification of the REA-equivalence types I to IV given in the recent work of Budaghyan and Kazymyrov (2012). Furthermore, we present the complexities of the verification of REA-equivalence types I and IV in the case basic simultaneous Gaussian elimination method is used. Next, we present two new REA-equivalence types V and VI with their complexities. Finally, we give the algorithms of each type I to VI with their MAGMA codes.