Statistical Techniques for Language Recognition: An Introduction and Guide for Cryptanalysts

Statistical Techniques for Language Recognition: An Introduction and Guide for Cryptanalysts (1993)

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by Ganesan

Venue:	Cryptologia
Citations:	10 - 2 self

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Datum	Value	Source
TITLE	Statistical Techniques for Language Recognition: An Introduction and Guide for Cryptanalysts	user correction - Legacy Corrections
AUTHOR NAME	Ganesan	user correction - Legacy Corrections
AUTHOR AFFIL	Security Planning and Research; Bell Atlantic	user correction - Legacy Corrections
AUTHOR ADDR	Beltsville, Maryland 20705	user correction - Legacy Corrections
ABSTRACT	We explain how to apply statistical techniques to solve several language-recognition problems that arise in cryptanalysis and other domains. Language recognition is important in cryptanalysis because, among other applications, an exhaustive key search of any cryptosystem from ciphertext alone requires a test that recognizes valid plaintext. Written for cryptanalysts, this guide should also be helpful to others as an introduction to statistical inference on Markov chains. Modeling language as a finite stationary Markov process, we adapt a statistical model of pattern recognition to language recognition. Within this framework we consider four welldefined language-recognition problems: 1) recognizing a known language, 2) distinguishing a known language from uniform noise, 3) distinguishing unknown 0th-order noise from unknown 1st-order language, and 4) detecting non-uniform unknown language. For the second problem we give a most powerful test based on the Neyman-Pearson Lemma. For the oth...	user correction - Legacy Corrections
YEAR	1993	INFERENCE
VENUE	Cryptologia	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	321--366	INFERENCE
VOLUME	4	INFERENCE
CITATIONS	94 found	ParsCit 1.0