Heuristic Language Analysis: Techniques and Applications

نویسنده

  • Jeremy Lennert
چکیده

In their 1993 paper, “Statistical Techniques for Language Recognition: An Introduction and Guide for Cryptanalysts,” Ganesan and Sherman present several statistical formulae useful for language recognition based on using a finite stationary Markov as a model to represent language. In my project, I verify the effectiveness of two of these formulae by examining the results when they are applied to various text samples of known entropy, and apply them to aid in automated ciphertext-only cryptanalysis of specific ciphers. My automated cryptanalysis program functions by generating possible decryption keys using language heuristics and applying one of the aforementioned formulae to analyze the resulting decryption. The program continues to generate possible decryption keys until the formula no longer shows an overall increase in the likelihood that the resulting text is natural English.

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تاریخ انتشار 2001