Modern Cryptography, Probabilistic Proofs and Pseudorandomness / Edition 1

Modern Cryptography, Probabilistic Proofs and Pseudorandomness / Edition 1

by Oded Goldreich
     
 

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ISBN-10: 354064766X

ISBN-13: 9783540647669

Pub. Date: 12/04/1998

Publisher: Springer Berlin Heidelberg

The book focuses on three related areas in the theory of computation. The areas are modern cryptography, the study of probabilistic proof systems, and the theory of computational pseudorandomness. The common theme is the interplay between randomness and computation. The book offers an introduction and extensive survey to each of these areas, presenting both the

Overview

The book focuses on three related areas in the theory of computation. The areas are modern cryptography, the study of probabilistic proof systems, and the theory of computational pseudorandomness. The common theme is the interplay between randomness and computation. The book offers an introduction and extensive survey to each of these areas, presenting both the basic notions and the most important (sometimes advanced) results. The presentation is focused on the essentials and does not elaborate on details. In some cases it offers a novel and illuminating perspective. The reader may obtain from the book 1. A clear view of what each of these areas is all above. 2. Knowledge of the basic important notions and results in each area. 3. New insights into each of these areas. It is believed that the book may thus be useful both to a beginner (who has only some background in the theory of computing), and an expert in any of these areas.

Product Details

ISBN-13:
9783540647669
Publisher:
Springer Berlin Heidelberg
Publication date:
12/04/1998
Series:
Algorithms and Combinatorics Series, #17
Edition description:
1999
Pages:
183
Product dimensions:
6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

Preface Chapter 1: The Foundations of Modern Cryptography 1.1 Introduction Part I: Basic Tools 1.2 Central Paradigms 1.2.1 Computational Difficulty 1.2.2 Computational Indistinguishability 1.2.3 The Simulation Paradigm 1.3 Pseudorandomness 1.3.1 The Basics 1.3.2 Pseudorandom Functions 1.4 Zero-Knowledge 1.4.1 The Basics 1.4.2 Some Variants Part II: Basic Utilities 1.5 Encryption 1.5.1 Definitions 1.5.2 Constructions 1.5.3 Beyond eavesdropping security 1.6 Signatures 1.6.1 Definitions 1.6.2 Constructions 1.6.3 Two variants 1.7 Cryptographic Prools 1.7.1 Definitions 1.7.2 Constructions Part III: Concluding Comments 1.8 Some Notes 1.8.1 General notes 1.8.2 Specific notes 1.9 Historical Perspective 1.10 Two Suggestions for Future Research 1.11 Some Suggestions for Further Reading Chapter 2: Probabilistic Proof Systems 2.1 Introduction 2.2 Interactive Proof Systems 2.2.1 Definition 2.2.2 The Role of Randomness 2.2.3 The Power of Interactive Proofs 2.2.4 The Interactive Proof System Hierarchy 2.2.5 How Powerful Should the Prover be? 2.3 Zero-Knowledge Proof Systems 2.3.1 A Sample Definition 2.3.2 The Power of Zero-Knowledge 2.3.3 The Role of Randomness 2.4 Probabilistically Checkable Proof Systems 2.4.1 Definition 2.4.2 The Power of Probabilistically Checkable Proofs 2.4.3 PCP and Approximation 2.4.4 More on PCP itself 2.4.5 The Role of Randomness 2.5 Other Probabilistic Proof Systems 2.5.1 Restricting the Provers Strategy 2.5.2 Non-Interactive Probabilistic Proofs 2.5.3 Proofs of Knowledge 2.5.4 Refereed Games 2.6 Concluding Remarks 2.6.1 Comparison among the various systems 2.6.2 The Story 2.6.3 Open Problems Chapter 3: Pseudorandom Generators 3.1 Introduction 3.2 The General Paradigm 3.3 The Archetypical Case 3.3.1 A Short Discussion 3.3.2 Some Basic Observations 3.3.3 Constructions 3.3.4 Pseudorandom Functions 3.4 Derandomization of time-complexity classes 3.5 Space Pseudorandom Generators 3.6 Special Purpose Generators 3.6.1 Pairwise-Independence Generators 3.6.2Small-Bias Generators 3.6.3 Random Walks on Expanders 3.6.4 Samplers 3.6.5 Dispersers, Extractors and Weak Random Sources 3.7 Concluding Remarks 3.7.1 Discussion 3.7.2 Historical Perspective 3.7.3 Open Problems Appendix A: Background on Randomness and Computation A.1 Probability Theory — Three Inequalities A.2 Computational Models and Complexity classes A.2.1 P, NP, and more A.2.2 Probabilistic Polynomial-Time A.2.3 Non-Uniform Polynomial-Time A.2.4 Oracle Machines A.2.5 Space Bounded Machines A.2.6 Average-Case Complexity A.3 Complexity classes — Glossary A.4 Some Basic Cryptographic Settings A.4.1 Encryption Schemes A.4.2 Digital Signatures and Message Authentication A.4.3 The RSA and Rabin Functions Appendix B: Randomized Computations B.1 Randomized Algorithms B.1.1 Approx. Counting of DNF satisfying assignments B.1.2 Finding a perfect matching B.1.3 Testing whether polynomials are identical B.1.4 Randomized Rounding applied to MaxSAT B.1.5 Primality Testing B.1.6 Testing Graph Connectivity via a random walk B.1.7 Finding minimum cuts in graphs B.2 Randomness in Complexity Theory B.2.1 Reducing (Approximate) Counting to Deciding B.2.2 Two-sided error versus one-sided error B.2.3 The permanent: Worst-Case vs Average Case B.3 Randomness in Distributed Computing B.3.1 Testing String Equality B.3.2 Routing in networks B.3.3 Byzantine Agreement B.4 Bibliographic Notes Appendix C: Notes on two proofs C.1 Parallel repetition of interactive proofs C.2 A generic Hard-Core Predicate C.2.1 A motivating discussion C.2.2 Back to the formal argument C.2.3 Improved Implementation of Algorithm $A Appendix D: Related Surveys by the Author Bibliography (over 300 entries) '

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