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Pseudorandomness and Cryptographic Applications (Princeton Computer Science Notes)

4.0 out of 5 stars 1 customer review
ISBN-13: 978-0691025469
ISBN-10: 0691025460
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Editorial Reviews

Amazon.com Review

Pseudorandomness and Cryptographic Applications, by Michael Luby, presents the mathematical underpinnings of one-way hash functions, which can be used to implement pseudorandom number generators. (These have a wide array of applications in cryptography.) After covering these basic mathematical ideas, the author delves into their applications in cryptosystems. Organized in 18 lectures, this book provides a mathematically intense treatise on the subject without much commentary in between. A set of exercises accompanies each chapter and a bibliography concludes the text. Filled with elegant mathematics, this is clearly a book for academic specialists.

From the Back Cover

A pseudorandom generator is an easy-to-compute function that stretches a short random string into a much longer string that "looks" just like a random string to any efficient adversary. One immediate application of a pseudorandom generator is the construction of a private key cryptosystem that is secure against chosen plaintext attack. There do not seem to be natural examples of functions that are pseudorandom generators. On the other hand, there do seem to be a variety of natural examples of another basic primitive: the one-way function. A function is one-way if it is easy to compute but hard for any efficient adversary to invert on average. The first half of the book shows how to construct a pseudorandom generator from any one-way function. Building on this, the second half of the book shows how to construct other useful cryptographic primitives, such as private key cryptosystems, pseudorandom function generators, pseudorandom permutation generators, digital signature schemes, bit commitment protocols, and zero-knowledge interactive proof systems. The book stresses rigorous definitions and proofs.

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Product Details

  • Series: Princeton Computer Science Notes
  • Paperback: 248 pages
  • Publisher: Princeton University Press (January 8, 1996)
  • Language: English
  • ISBN-10: 0691025460
  • ISBN-13: 978-0691025469
  • Product Dimensions: 6 x 0.6 x 9 inches
  • Shipping Weight: 13.6 ounces (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #3,455,570 in Books (See Top 100 in Books)

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By Dr. Lee D. Carlson HALL OF FAMEVINE VOICE on March 25, 2001
Format: Paperback
Walking into a colleague's office and noticing papers scattered all over her desk and shelves, I remarked on the apparent disorganization. She explained that from her standpoint everything was organized and easy to find. Randomness, she said, is observer dependent.
This is the theme taken in this book, namely tha a proper concept of randomness is not an intrinsic property of a collection or a distribution, but rather is dependent of the tools and computing capabilities of the observer. The concept of a pseudorandom distribution is introduced as a distribution where no efficient procedure or program can distinguish it from a uniform distribution. Pseudorandom generators are polynomial-time deterministic programs that take a randomly selected seed and expand it into a pseudorandom bit sequence.
The preliminaries/introduction gives an overview of sets, set functions, big-O, little-o notation, and most importantly from the author's standpoint, function and probability ensembles. He defines what it means to have a source of random bits, but does not give algorithms on how to produce them. Complexity classes are also discussed for both the deterministic and probabilistic cases, along with a very brief review of probability.
Private key cryptosystems begin the next chapter with an example of a one-time-pad private key cryptosystems. Pseudorandom generators are introduced as a solution to the problem of sending secure messages that are longer than the private key.
The author does a good job of defining computational and statistical indistinguishability, and the connection between 1-way functions and pseudorandom generators.
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