This is a central topic in any computer science curriculum. To distinguish this textbook from others, the author considers probabilistic methods as being fundamental for the construction of simple and efficient algorithms, and in each chapter at least one problem is solved using a randomized algorithm. Data structures are discussed to the extent needed for the implementation of the algorithms. The specific algorithms examined were chosen because of their wide field of application. This book originates from lectures for undergraduate and graduate students. The text assumes experience in programming algorithms, especially with elementary data structures such as chained lists, queues, and stacks. It also assumes familiarity with mathematical methods, although the author summarizes some basic notations and results from probability theory and related mathematical terminology in the appendices. He includes many examples to explain the individual steps of the algorithms, and he concludes each chapter with numerous exercises.

The first part of this book covers the key concepts of cryptography on an undergraduate level, from encryption and digital signatures to cryptographic protocols. Essential techniques are demonstrated in protocols for key exchange, user identification, electronic elections and digital cash. In the second part, more advanced topics are addressed, such as the bit security of one-way functions and computationally perfect pseudorandom bit generators. The security of cryptographic schemes is a central topic. Typical examples of provably secure encryption and signature schemes and their security proofs are given. Though particular attention is given to the mathematical foundations, no special background in mathematics is presumed. The necessary algebra, number theory and probability theory are included in the appendix. Each chapter closes with a collection of exercises. In the second edition the authors added a complete description of the AES, an extended section on cryptographic hash functions, and new sections on random oracle proofs and public-key encryption schemes that are provably secure against adaptively-chosen-ciphertext attacks. The third edition is a further substantive extension, with new topics added, including: elliptic curve cryptography; Paillier encryption; quantum cryptography; the new SHA-3 standard for cryptographic hash functions; a considerably extended section on electronic elections and Internet voting; mix nets; and zero-knowledge proofs of shuffles. The book is appropriate for undergraduate and graduate students in computer science, mathematics, and engineering.

Due to the rapid growth of digital communication and electronic data exchange, information security has become a crucial issue in industry, business, and administration. Modern cryptography provides essential techniques for securing information and protecting data. In the first part, this book covers the key concepts of cryptography on an undergraduate level, from encryption and digital signatures to cryptographic protocols. Essential techniques are demonstrated in protocols for key exchange, user identification, electronic elections and digital cash. In the second part, more advanced topics are addressed, such as the bit security of one-way functions and computationally perfect pseudorandom bit generators. The security of cryptographic schemes is a central topic. Typical examples of provably secure encryption and signature schemes and their security proofs are given. Though particular attention is given to the mathematical foundations, no special background in mathematics is presumed. The necessary algebra, number theory and probability theory are included in the appendix. Each chapter closes with a collection of exercises. The second edition contains corrections, revisions and new material, including a complete description of the AES, an extended section on cryptographic hash functions, a new section on random oracle proofs, and a new section on public-key encryption schemes that are provably secure against adaptively-chosen-ciphertext attacks.

This is a central topic in any computer science curriculum. To distinguish this textbook from others, the author considers probabilistic methods as being fundamental for the construction of simple and efficient algorithms, and in each chapter at least one problem is solved using a randomized algorithm. Data structures are discussed to the extent needed for the implementation of the algorithms. The specific algorithms examined were chosen because of their wide field of application. This book originates from lectures for undergraduate and graduate students. The text assumes experience in programming algorithms, especially with elementary data structures such as chained lists, queues, and stacks. It also assumes familiarity with mathematical methods, although the author summarizes some basic notations and results from probability theory and related mathematical terminology in the appendices. He includes many examples to explain the individual steps of the algorithms, and he concludes each chapter with numerous exercises.

Lernen Sie in diesem Buch mehr uber Algorithmen und Datenstrukturen In diesem Lehrbuch werden Algorithmen und Datenstrukturen exakt aber auch anschaulich und nachvollziehbar vermittelt, denn Algorithmen sind heute allgegenwartig und vielfaltig. Sie sind Gegenstand intensiver Forschung und zahlen zu den fundamentalen Konzepten der Informatik. Dieses Buch uber Algorithmen und Datenstrukturen ist aus Vorlesungen fur Studierende der Informatik sowie der Medien- und Wirtschaftsinformatik an der Technischen Hochschule Nurnberg entstanden. Die grundlegenden Themen werden in den Bachelorkursen behandelt. Fortgeschrittene Teile, wie zum Beispiel die probabilistischen Algorithmen, stammen dagegen aus Masterkursen. Der Inhalt des Werks im UEberblick Im ersten Kapitel seines Buchs uber Algorithmen und Datenstrukturen fuhrt Knebl relevante Grundlagen und Designprinzipien fur Algorithmen ein. Die anschliessenden Kapitel 2 - 6 sind nach Problembereichen organisiert: Sortieren und Suchen (2), Hashverfahren (3), Baume zur Speicherung von Daten und zur Datenkomprimierung (4), fundamentale Graphenalgorithmen, wie Tiefen- und Breitensuche und Anwendungen davon (5), die Berechnung von minimalen aufspannenden Baumen und von kurzesten Wegen in gewichteten Graphen als auch die Loesung des Flussproblems in Netzwerken (6). Probabilistische Methoden sind grundlegend fur einfache sowie effiziente Algorithmen und Datenstrukturen. Deshalb wird in jedem Kapitel dieses Buchs mindestens ein Problem mit einem probabilistischen Algorithmus geloest. Die notwendigen mathematischen Grundlagen werden im ersten Kapitel sowie im Anhang entwickelt. Loesungen zu den zahlreichen UEbungsaufgaben stehen Ihnen bequem zum Download bereit.