Modern Cryptography, Probabilistic Proofs and Pseudorandomness

1. Auflage. Softcover version of original hardcover Auflage 1999
ISBN: 978-3-642-08432-4
Verlag: Springer

Buch, Englisch, Band 17, 183 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 318 g

Reihe: Algorithms and Combinatorics

You can start by putting the DO NOT DISTURB sign. Cay, in Desert Hearts (1985). The interplay between randomness and computation is one of the most fas­ cinating scientific phenomena uncovered in the last couple of decades. This interplay is at the heart of modern cryptography and plays a fundamental role in complexity theory at large. Specifically, the interplay of randomness and computation is pivotal to several intriguing notions of probabilistic proof systems and is the focal of the computational approach to randomness. This book provides an introduction to these three, somewhat interwoven domains (i.e., cryptography, proofs and randomness). Modern Cryptography. Whereas classical cryptography was confined to the art of designing and breaking encryption schemes (or "secrecy codes"), Modern Cryptography is concerned with the rigorous analysis of any system which should withstand malicious attempts to abuse it. We emphasize two aspects of the transition from classical to modern cryptography: ( 1) the wide­ ning of scope from one specific task to an utmost wide general class of tasks; and (2) the move from an engineering-art which strives on ad-hoc tricks to a scientific discipline based on rigorous approaches and techniques.

Zielgruppe

Research

Autoren/Hrsg.

Goldreich, Oded

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Kryptologie, Informationssicherheit
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Kryptographie, Datenverschlüsselung

Inhaltsverzeichnis

1. The Foundations of Modern Cryptography.- 2. Probabilistic Proof Systems.- 3. Pseudorandom Generators.- 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.- 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.- C. 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.- D. Related Surveys by the Author.