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Machine learning is definitely applicable in analyzing simple shift ciphers like Caesar and affine ciphers, as well as substitution ciphers like Vigenère, but is it possible for machine learning to solve problems involving more complex ciphers such as Hill ciphers, where characters are mixed up and ruin frequency analysis?

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    $\begingroup$ Could you provide applicable examples? $\endgroup$ – kelalaka Aug 22 at 21:46
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    $\begingroup$ what does machine learning do that classical statistics can't on those simple ciphers? if you can link to demonstrations of superiority, you might be taken more seriously. $\endgroup$ – kodlu Aug 22 at 22:30
  • $\begingroup$ @abcdefghijklmnop151 I want to hear how machine learning can be applied to breaking a double transposition when the second one is disrupted as in the VIC cipher. $\endgroup$ – Patriot Aug 23 at 10:10
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    $\begingroup$ @Patriot I wouldn't be surprised if basic ML could break that. $\endgroup$ – forest Sep 4 at 2:20
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A cryptanalyst finds the right key for decryption, while a machine learning model finds a suitable solution in a large space of possible solutions. With enough data, the machine learning model could find a good solution. How much data is needed to reliably use machine learning for breaking complex ciphers such that it's less work than brute-force search could be a challenge.

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