Written by one of the developers of the technology, Hashing is both a historical document on the development of hashing and an analysis of the applications of hashing in a society increasingly concerned with security. The material in this book is based on courses taught by the author, and key points are reinforced in sample problems and an accompanying instructor's manual. Graduate students and researchers in mathematics, cryptography, and security will benefit from this overview of hashing and the complicated mathematics that it requires.
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Alan G. Konheim, PhD, is Professor Emeritus of Computer Science at the University of Californa, Santa Barbara. Dr. Konheim’s early work at IBM led to the Data Encryption Standard (DES), which was evaluated by his Yorktown Probability and Cryptography Group. DES was certified as a national standard in the 1970s. Dr. Konheim continues to consult the government in the area of cryptanalysis.
Gain the Skills and Knowledge Needed to Understanding Data Security Systems
A file of computer data is composed of records to each of which a key or identifier is associated. The key is used to search for the address of a desired record. When the file is a telephone directory, searching is easy—the key is the subscriber’s name and the records are naturally arranged in alphabetic order. For data whose records are not easily alphabetized, a hash function is used to arithmetically derive from the key record’s address. Hashing was invented during the design of the IBM 701 machine in the 1950s by Hans Peter Luhn. In the ensuing half century, the hashing concept has found a variety of applications. When combined with cryptography, hashing can be used to authenticate users in e-commerce on the Web.
Professor Konheim is an authority on computer security and an early contributor to hashing technology. Based on courses taught by the author, this book unravels the complicated mathematics involved in hashing as it explains in detail the various hashing methods. It describes:
Key points are reinforced in the sample problems and solutions provided; also included are an accompanying instructor’s manual and extensive bibliography. Hashing in Computer Science is valuable reading for graduate students and researchers in mathematics, cryptography, and security. It can be used as a textbook in senior and graduate courses on cryptography and others that employ cryptanalysis, computer security, analysis of randomized and combinatorial algorithms, computer networks, compiler design, computational geometry, and theory of computation.
Gain the Skills and Knowledge Needed to Understanding Data Security Systems
A file of computer data is composed of records to each of which a key or identifier is associated. The key is used to search for the address of a desired record. When the file is a telephone directory, searching is easy—the key is the subscriber’s name and the records are naturally arranged in alphabetic order. For data whose records are not easily alphabetized, a hash function is used to arithmetically derive from the key record’s address. Hashing was invented during the design of the IBM 701 machine in the 1950s by Hans Peter Luhn. In the ensuing half century, the hashing concept has found a variety of applications. When combined with cryptography, hashing can be used to authenticate users in e-commerce on the Web.
Professor Konheim is an authority on computer security and an early contributor to hashing technology. Based on courses taught by the author, this book unravels the complicated mathematics involved in hashing as it explains in detail the various hashing methods. It describes:
Key points are reinforced in the sample problems and solutions provided; also included are an accompanying instructor’s manual and extensive bibliography. Hashing in Computer Science is valuable reading for graduate students and researchers in mathematics, cryptography, and security. It can be used as a textbook in senior and graduate courses on cryptography and others that employ cryptanalysis, computer security, analysis of randomized and combinatorial algorithms, computer networks, compiler design, computational geometry, and theory of computation.
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