Cipher type detection

5Citations
Citations of this article
76Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Manual analysis and decryption of enciphered documents is a tedious and error prone work. Often-even after spending large amounts of time on a particular cipher-no decipherment can be found. Automating the decryption of various types of ciphers makes it possible to sift through the large number of encrypted messages found in libraries and archives, and to focus human effort only on a small but potentially interesting subset of them. In this work, we train a classifier that is able to predict which encipherment method has been used to generate a given ciphertext. We are able to distinguish 50 different cipher types (specified by the American Cryptogram Association) with an accuracy of 58.5%. This is a 11.2% absolute improvement over the best previously published classifier.

Cite

CITATION STYLE

APA

Nuhn, M., & Knight, K. (2014). Cipher type detection. In EMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (pp. 1769–1773). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/d14-1185

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free