Cryptosystems are used to provide security in communications and data transmissions. Stream ciphers are private key systems that are often used to transform large volumn data. In order to have security, key streams used in stream ciphers must be fully analyzed so that they do not contain specific patterns, statistical infomation and structures with which attackers are able to quickly recover the entire key streams and then break down the systems. Based on different schemes to generate sequences and different ways to represent them, there are a variety of stream cipher analyses. The most important one is the linear analysis based on linear feedback shift registers (LFSRs) which have been extensively studied since the 1960's. Every sequence over a finite field has a well defined linear complexity. If a sequence has small linear complexity, it can be efficiently recoverd by Berlekamp-Messay algorithm. Therefore, key streams must have large linear complexities. A lot of work have been done to generate and analyze sequences that have large linear complexities. In the early 1990's, Klapper and Goresky discovered feedback with carry shift registers over Z/(p) (p-FCSRS), p is prime. Based on p-FCSRs, they developed a stream cipher analysis that has similar properties to linear analysis. For instance, every sequence over Z/(p) has a well defined p-adic complexity and key streams of small p-adic complexity are not secure for use in stream ciphers. This disstation focuses on stream cipher analysis based on feedback with carry shift registers. The first objective is to develop a stream cipher analysis based on feedback with carry shift registers over Z/(N) (N-FCSRs), N is any integer greater than 1, not necessary prime. The core of the analysis is a new rational approximation algorithm that can be used to efficiently compute rational representations of eventually periodic N-adic sequences. This algorithm is different from that used in $p$-adic sequence analysis which was given by Klapper and Goresky. Their algorithm is a modification of De Weger's rational approximation algorithm. The second objective is to generalize feedback with carry shift register architecture to more general algebraic settings which are called algebraic feedback shift registers (AFSRs). By using algebraic operations and structures on certain rings, we are able to not only construct feedback with carry shift registers, but also develop rational approximation algorithms which create new analyses of stream ciphers. The cryptographic implication of the current work is that any sequences used in stream ciphers must have large N-adic complexities and large AFSR-based complexities as well as large linear complexities.

An α-approximation algorithm is an algorithm guaranteed to output a solutionthat is within an α ratio of the optimal solution. We are interested in thefollowing question: Given an NP-hard optimization problem, what is the bestapproximation guarantee that any polynomial time algorithm could achieve? We mostly focus on studying the approximability of two classes of NP-hardproblems: Constraint Satisfaction Problems (CSPs) and Computational Learning Problems. For CSPs, we mainly study the approximability of MAX CUT, MAX 3-CSP,MAX 2-LINR, VERTEX-PRICING, as well as serval variants of the UNIQUEGAMES.• The problem of MAX CUT is to find a partition of a graph so as to maximizethe number of edges between the two partitions. Assuming theUnique Games Conjecture, we give a complete characterization of the approximationcurve of the MAX CUT problem: for every optimum value ofthe instance, we show that certain SDP algorithm with RPR2 roundingalways achieve the optimal approximation curve.• The input to a 3-CSP is a set of Boolean constraints such that each constraintcontains at most 3 Boolean variables. The goal is to find an assignmentto these variables to maximize the number of satisfied constraints.We are interested in the case when a 3-CSP is satisfiable, i.e.,there does exist an assignment that satisfies every constraint. Assumingthe d-to-1 conjecture (a variant of the Unique Games Conjecture), weprove that it is NP-hard to give a better than 5/8-approximation for theproblem. Such a result matches a SDP algorithm by Zwick which givesa 5/8-approximation problem for satisfiable 3-CSP. In addition, our resultalso conditionally resolves a fundamental open problem in PCP theory onthe optimal soundness for a 3-query nonadaptive PCP system for NP withperfect completeness.• The problem of MAX 2-LINZ involves a linear systems of integer equations;these equations are so simple such that each equation contains atmost 2 variables. The goal is to find an assignment to the variables so asto maximize the total number of satisfied equations. It is a natural generalizationof the Unique Games Conjecture which address the hardness ofthe same equation systems over finite fields. We show that assuming theUnique Games Conjecture, for a MAX 2-LINZ instance, even that thereexists a solution that satisfies 1−ε of the equations, it is NP-hard to findone that satisfies ² of the equations for any ε > 0.

In this thesis we focus on two NP-hard and intensively studied problems: The travelling salesman problem (TSP), which aims to find a minimum cost tour that visits every node exactly once in a complete weighted graph, and the 2-edge-connected spanning subgraph problem (2ECSS), which aims to find a minimum size 2-edge-connected spanning subgraph in a given graph. TSP and 2ECSS have many real world applications. However, both problems are NP-hard which means it is unlikely that polynomial time algorithms exist to solve them, so methods that return close to optimal solutions are sought. In this thesis we mainly focus on k-approximation algorithms for the two problems, which efficiently return a solution within k times of the optimal solution. For a special case of TSP called graph TSP, using ideas from Momke and Svensson, we present a 25/18-approximation algorithm for a special class of graphs using circulations and T-joins, which improves the previous known best bound of 7/5 for such graphs. Moreover, if the graph does not contain special nodes, our algorithm ensures the ratio of 4/3. For 2ECSS, given any k-edge-connected graph G=(V,E), |V|=n, |E|=m, we present an approximation algorithm that gives a 2-edge-connected spanning subgraph with the number of edges at most n+(m-n)/(k-1)-(k-2)/(k-1) with a novel use of circulations, which improves both the approximation ratio and the simplicity of the proof compared to a result by Huh in 2004.

Orientador: Orlando Lee / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-25T08:59:09Z (GMT). No. of bitstreams: 1 Reis_MarcioFelix_M.pdf: 1988657 bytes, checksum: 6ee5ea6ba406aea3ccb7e3332e679eab (MD5) Previous issue date: 2014 / Resumo: Neste trabalho estudamos o problema da árvore geradora com muitas folhas (PAGMF). Este problema pode ser usado como abstração para diversos problemas práticos e sabe-se que é NP-difícil. Estudamos, implementamos e executamos testes para algoritmos aproximados e exatos para o PAGMF e para um caso particular que considera apenas grafos cúbicos. O principal objetivo do trabalho foi verificar o comportamento prático dos algoritmos estudados. Para as instâncias testadas, em geral, o algoritmo guloso apresentou melhores resultados para o PAGMF e o algoritmo 2-aproximado teve os melhores resultados para os grafos cúbicos / Abstract: In this work we study the maximum leaf spanning tree problem (MLSTP). This problem can be used as an abstraction for many practical problems and is known to be NP-hard. We studied, implemented and executed tests for approximate and exact algorithms for the MLSTP and for a particular case that considers only cubic graphs. The main objective of this study was to investigate the practical behavior of the algorithms studied. For the tested instances, in general, the greedy algorithm showed better results for the MLSTP and the 2-approximate algorithm had the best results for cubic graphs / Mestrado / Ciência da Computação / Mestre em Ciência da Computação

The Metric Travelling Salesman Problem, henceforth metric TSP, is a fundamental problem in combinatorial optimization which consists of finding a minimum cost Hamiltonian cycle (also called a TSP tour) in a weighted complete graph in which the costs are metric. Metric TSP is known to belong to a class of problems called NP-hard even in the special case of graph-TSP, where the metric costs are based on a given graph. Thus, it is highly unlikely that efficient methods exist for solving large instances of these problems exactly. In this thesis, we develop a new heuristic for metric TSP based on extending ideas successfully used by Mömke and Svensson for the special case of graph-TSP to the more general case of metric TSP. We demonstrate the efficiency and usefulness of our heuristic through empirical testing. Additionally, we turn our attention to graph-TSP. For this special case of metric TSP, there has been much recent progress with regards to improvements on the cost of the solutions. We find the exact value of the ratio between the cost of the optimal TSP tour and the cost of the optimal subtour linear programming relaxation for small instances of graph-TSP, which was previously unknown. We also provide a simplified algorithm for special graph-TSP instances based on the subtour linear programming relaxation.

In this thesis we focus on two NP-hard and intensively studied problems: The travelling salesman problem (TSP), which aims to find a minimum cost tour that visits every node exactly once in a complete weighted graph, and the 2-edge-connected spanning subgraph problem (2ECSS), which aims to find a minimum size 2-edge-connected spanning subgraph in a given graph. TSP and 2ECSS have many real world applications. However, both problems are NP-hard which means it is unlikely that polynomial time algorithms exist to solve them, so methods that return close to optimal solutions are sought. In this thesis we mainly focus on k-approximation algorithms for the two problems, which efficiently return a solution within k times of the optimal solution. For a special case of TSP called graph TSP, using ideas from Momke and Svensson, we present a 25/18-approximation algorithm for a special class of graphs using circulations and T-joins, which improves the previous known best bound of 7/5 for such graphs. Moreover, if the graph does not contain special nodes, our algorithm ensures the ratio of 4/3. For 2ECSS, given any k-edge-connected graph G=(V,E), |V|=n, |E|=m, we present an approximation algorithm that gives a 2-edge-connected spanning subgraph with the number of edges at most n+(m-n)/(k-1)-(k-2)/(k-1) with a novel use of circulations, which improves both the approximation ratio and the simplicity of the proof compared to a result by Huh in 2004.

Neste projeto estudamos algoritmos de aproximação para o problema da árvore de Steiner com coleta de prêmios. Trata-se de uma generalização do problema da árvore de Steiner, onde é dado um grafo com custos positivos nas arestas e penalidades positivas nos vértices. O objetivo é encontrar uma subárvore do grafo que minimize a soma dos custos das arestas mais a soma das penalidades dos vértices que não pertencem à subárvore. Em 2009, os autores Archer, Bateni, Hajiaghayi e Karloff obtiveram pela primeira vez um algoritmo com fator de aproximação estritamente menor do que 2. Além de analisarmos este algoritmo, estudamos também a implementação de algoritmos 2-aproximação para o problema da árvore de Steiner e da árvore de Steiner com coleta de prêmios. / In this project we analyze approximation algorithms for the prize-collecting Steiner tree problem. This is a generalization of the Steiner tree problem, in which it is given a graph with positive costs in edges and positive penalties in vertices. The goal is to find a subtree of the graph that minimizes the sum of costs of edges plus the sum of the penalties of the vertices that don\'t belong to the subtree. In 2009, the authors Archer, Bateni, Hajiaghayi e Karloff described, for the first time an algorithm with approximation factor strictly less than 2. Besides analyzing this algorithm, we also study the implementation of 2-approximation algorithms to the Steiner tree problem and prize-collecting Steiner tree problem.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第18530号 / 情博第534号 / 新制||情||95(附属図書館) / 31416 / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 岡部 寿男, 教授 松山 隆司, 教授 阿久津 達也 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

O foco central desta tese é o desenvolvimento de algoritmos para o problema de recoloração convexa de caminhos. Neste problema, é dado um caminho cujos vértices estão coloridos arbitrariamente, e o objetivo é recolorir o menor número possível de vértices de modo a obter uma coloração convexa. Dizemos que uma coloração de um grafo é convexa se, para cada cor, o subgrafo induzido pelos vértices dessa cor é conexo. Sabe-se que este problema é NP-difícil. Associamos a este problema um poliedro, e estudamos sua estrutura facial, com vistas ao desenvolvimento de um algoritmo. Mostramos várias inequações válidas para este poliedro, e provamos que várias delas definem facetas. Apresentamos um algoritmo de programação dinâmica que resolve em tempo polinomial o problema da separação para uma classe grande de inequações que definem facetas. Implementamos um algoritmo branch-and-cut baseado nesses resultados, e realizamos testes computacionais com instâncias geradas aleatoriamente. Apresentamos adicionalmente uma heurística baseada numa formulação linear que obtivemos. Estudamos também um caso especial deste problema, no qual as instâncias consistem em caminhos coloridos, onde cada cor ocorre no máximo duas vezes. Apresentamos um algoritmo de 3/2-aproximação para este caso, que é também NP-difícil. Para o caso geral, é conhecido na literatura um algoritmo de 2-aproximação. / The focus of this thesis is the design of algorithms for the convex recoloring problem on paths. In this problem, the instance consists of a path whose vertices are arbitrarily colored, and the objective is to recolor the least number of vertices so as to obtain a convex coloring.Acoloring of a graph is convex if, for each color, the subgraph induced by the vertices of this color is connected. This problem is known to be NP-hard. We associate a polyhedron to this problem and investigate its facial structure. We show various classes of valid inequalities for this polyhedron and prove that many of them define facets.We present a polynomial-time dynamic programming algorithm that solves, in polynomial time, the separation problem for a large class of facet-defining inequalities.We report on the computational experiments with a branch-and-cut algorithm that we propose for the problem. Additionally, we present a heuristic that is based on a linear formulation for the problem. We also study a special case of this problem, restricted to instances consisting of colored paths in which each color occurs at most twice. For this case, which is also NP-hard, we present a 3/2-approximation algorithm. For the general case, it is known a 2-approximation algorithm.

Nesta dissertação estudamos --- do ponto de vista algorítmico --- o seguinte problema, conhecido como problema da partição conexa balanceada. Dado um grafo conexo G com pesos atribuídos a seus vértices, e um inteiro q >= 2, encontrar uma partição dos vértices de G em q classes, de forma que cada classe da partição induza um grafo conexo e que, ao considerar as somas dos pesos dos vértices de cada classe, a menor das somas seja o maior possível. Em outras palavras, o objetivo é encontrar q classes cujos pesos sejam tão balanceados quanto possível. Sabe-se que este problema é NP-difícil. Mencionamos alguns resultados sobre complexidade computacional e algoritmos que são conhecidos para este problema. Apresentamos algumas heurísticas que desenvolvemos, todas elas baseadas no uso do algoritmo polinomial para árvores, devido a Perl e Schach, que apresentamos com detalhe. Implementamos quatro heurísticas e um algoritmo de 3/4-aproximação conhecido para o caso q=2. Exibimos os resultados obtidos com os vários testes computacionais conduzidos com instâncias aleatórias, com grafos de diferentes pesos e densidades. Os resultados computacionais indicam que o desempenho dessas heurísticas --- todas elas polinomiais --- é bem satisfatório. No caso especial em que q=2, observamos que a heurística mais onerosa sistematicamente produziu soluções melhores ou iguais às do algoritmo de aproximação / In this dissertation we study algorithmic aspects of the following problem, known as the balanced connected partition. Given a connected graph G with weights defined on its vertices, and an integer q >= 2, find a partition of the vertices of G into q classes such that each class induces a connected graph, and furthermore, when we consider the sum of the weights of the vertices in each class, the smallest sum is as large as possible. In other words, the q classes must have weights that are as balanced as possible. This problem is known to be NP-hard. We mention some computational complexity and algorithmic results that are known for this problem. We present some heuristics that we designed, all of them based on the use of the polynomial algorithm for trees, due to Perl and Schach, which we show in detail. We implemented four heuristics and a 3/4-approximation algorithm that is known for q=2. We run tests on many random instances, of graphs with different weights and densities. The computational results indicate that the performance of these heuristics --- all of polynomial time complexity --- are very satisfactory. For q=2, we observed that the most expensive heuristic produced solutions with values which are systematically better or equal to those produced by the approximation algorithm.