# Leierzopf 2021: A Massive Machine-Learning Approach For Classical Cipher Type Detection Using Feature Engineering

> Ernst Leierzopf, Nils Kopal, Bernhard Esslinger et al., 2021. 3 records on Mysteries Department cite it. The inductive methods survey notes that…

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# A Massive Machine-Learning Approach For Classical Cipher Type Detection Using Feature Engineering

Ernst Leierzopf, Nils Kopal, Bernhard Esslinger et al., 2021. _International Conference on Historical Cryptology_.

Tests whether machine-learning classifiers using hand-built ciphertext features can tell apart 56 cipher types defined by the American Cryptogram Association, with neural networks doing best.

**Voynich Manuscript** Articledoi: **[10.3384/ecp183164](https://doi.org/10.3384/ecp183164)** Checked against the original0

## What it's used for here

The inductive methods survey notes that cipher-type classifiers like this one have no training class for verbose, mixed-key or generated text, which limits their use here.

## Cited by on this site 3 records

[3 methods surveys]

Cryptanalysis, linguistics, inductive methods

SRC

## Cite it

```
Leierzopf, E., Kopal, N., Esslinger, B., Lampesberger, H., & Hermann, E. (2021). A Massive Machine-Learning Approach For Classical Cipher Type Detection Using Feature Engineering. International Conference on Historical Cryptology. https://doi.org/10.3384/ecp183164
```

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