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Asked: 2026-05-22T03:10:28+00:00

I have already worked with Neural Networks before and know most basics about them.

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I have already worked with Neural Networks before and know most basics about them. I especially have experience with regular Multi-Layer-Perceptrons. I was now asked by someone if the following is possible and somehow feel challenged to master the problem 🙂

The Situation

Let’s assume I have a program that can encrypt and decrypt regular ASCII-Coded Files. I have no idea at all about the specific encryption method nor the key used. All I know is, that the program can reverse the encryption and thus read the original content.

What I want?

Now my question is: Do you think it is possible to train (some kind of) Neural Network which replicates the exact decryption-Algorithm with acceptable effort?

My ideas and work so far

I have not much of experience with encryption. Someone suggested just to assume AES encryption, so I could write a little program to batch-encrypt ASCII-Coded files. So this would cover the gathering of learning data for supervised learning. Using the encrypted files als input for the neural networks and the original files as training data I could train any net. But now I am stuck, how would you suggest to feed the input and output data to the Neural Network. So how many Input and Output-Neurons would you guys use?
Since I have no Idea what the encrypted files would look like, it might be the best idea to pass the data in binary form. But I can’t just use thousands of input and output-neurons and pass all bits at the same time. Maybe recurrent networks and feed one bit after another? Also doesn’t sound very effective.

Another problem is, that you can’t decrypt partially – meaning you can’t be roughly correct. You either got it right or not. To put it other words, in the end the net error has to be zero. From what I have experienced so far with ANN, this is nearly impossible to achieve for big networks. So is this problem solvable?

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1 Answer

  1. Editorial Team

    Another problem is, that you can’t decrypt partially – meaning you can’t be roughly correct. You either got it right or not.

    That’s exactly the problem. Neural Networks can approximate continuous functions, meaning that a small change in the input values causes a small change in the output value, while encryption functions/algorithm are designed to be as non-continuous as possible.

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