# Book:Dominic Welsh/Codes and Cryptography

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## Dominic Welsh:

## Dominic Welsh: *Codes and Cryptography*

Published $\text {1988}$, **Oxford University Press**

- ISBN 0-19-853287-3

### Subject Matter

### Contents

- Preface

- Notation

- 1. Entropy = Uncertainty = Information
- 1. Uncertainty
- 2. Entropy and its properties
- 3. Conditional entropy
- 4. Information
- 5. Conclusion

- 2. The noiseless coding theorem for memoryless sources
- 1. Memoryless sources
- 2. Instantaneous and uniquely decipherable codes
- 3. The Kraft-McMillan inequalities
- 4. The noiseless coding theorem for memoryless sources
- 5. Constructing compact codes

- 3. Communication through noisy channels
- 1. The discrete memoryless channel
- 2. Connecting the source to the channel
- 3. Codes and decoding rules
- 4. The capacity of a channel
- 5. The noisy coding theorem
- 6. Capacity is the bound to accurate communication

- 4. Error-correcting codes
- 1. The coding problem
- 2. The sphere-packing and Gilbert-Varshamov Bounds; perfect codes
- 3. Linear codes
- 4. Using linear codes
- 5. Minimum-distance decoding for linear codes
- 6. Binary Hamming codes
- 7. Cyclic codes
- 8. The Mariner code; Reed Muller codes
- 9. Conclusion

- 5. General sources
- 1. The entropy of a general source
- 2. Stationary sources
- 3. Typical messages of a memoryless source
- 4. Typical messages of general sources -- ergodicity
- 5. Markov sources
- 6. The coding theorems for ergodic sources

- 6. The structure of natural languages
- 1. English as a mathematical source
- 2. The entropy of English
- 3. Zipf's law and word entropy
- 4. The redundancy of a language

- 7. Cryptosystems
- 1. Basic principles
- 2. Breaking a cryptosystem
- 3. Equivocation and perfect secrecy
- 4. Combining cryptosystems
- 5. Unicity
- 6. Hellman's extension of linear shift-register sequences
- 7. Conclusion

- 8. The one-time pad and linear shift-register sequences
- 1. The one-time pad
- 2. Linear shift-register sequences
- 3. The insecurity of linear shift-register sequences
- 4. Generating cyclic codes

- 9. Computational complexity
- 1. The intrinsic difficulty of a problem: examples
- 2. P = Polynomial time
- 3. NP = Nondeterministic Polynomial time
- 4. NP-complete/hard problems
- 5. Circuit complexity
- 6. Randomized algorithms
- 7. Effective versus intractable computations

- 10. One-way functions
- 1. Informal approach: the password problem
- 2. Using NP-hard problems as cryptosystems
- 3. The Data Encryption Standard (DES)
- 4. The discrete logarithm
- 5. Using the discrete logarithm to solve the key-distribution problem
- 6. A cryptosystem with no keys
- 7. On the difficulty of factoring and taking discrete logarithms

- 11. Public key cryptosystems
- 1. The idea of a trapdoor function
- 2. The Rivest-Shamir-Adleman (RSA) system
- 3. Knapsack-based systems
- 4. A public-key system as intractable as factoring
- 5. A public-key system based on the discrete logarithm
- 6. Error-correcting codes as a public-key system

- 12. Authentication and digital signatures
- 1. Introduction
- 2. Authentication in a communication system
- 3. Signature schemes based on conventional cryptosystems
- 4. Using public key networks to send signed messages
- 5. Faster signatures but less privacy
- 6. Attacks and cracks in trapdoor signature schemes

- 13. Randomized encryption
- 1. Introduction
- 2. Semantic security and the Goldwasser-Micali scheme
- 3. Cryptographically secure pseudo-random numbers
- 4. Wyner's wiretap channel
- 5. Effective entropy

- Appendices
- 1. Proof of the uniqueness theorem that $H = -\sum p_i \log p_i$
- 2. Letter frequencies of English

- Answers to exercises

- Answers and hints to problems

- References

- Index

## Source work progress

- 1988: Dominic Welsh:
*Codes and Cryptography*... (previous) ... (next): $\S 1$: Entropy = uncertainty = information: $1.1$ Uncertainty: Exercises $1.1$: $2.$