One of the approaches I have been searching so far is the application of utilizing Neural Network to classify Spectrogram images, which is heavily used in speech recognition.
I am conducting an experiment to identify the similarities of binary executable (raw 0s and 1s), and planning to deploy the same concept of speech recognition on binary executable. I have been preparing the executable with the following criteria:
1- The sampling rate is 8 KHz.
2- The bit Depth is 8-Bits. This means that each sample's amplitude will be represented using 1 Byte.
I am being stuck in generating the Spectrogram. Now my background is networks and programming and I have been doing a lot of research to generate it. The challenge is the identification of the frequencies of the samples I have in order to have the 3-dimensions of spectrogram (frequency, time and amplitude). I did a research, where FFT can be used to generate the frequency domain from the time domain, but not sure if it is feasible for binary executable.
Python supports .wave files spectrogram plotting, but the files I have are executable and not music or sound.
1- Can I identify the used frequencies in my binary by having the sampling rate and amplitude?
2- Can I generate a spectrogram of an executable binary, even if it is NOT originally speech or music?
3- Is there any tool/code that I can utilize for the spectrogram generation?