https://stackoverflow.com/questions/2979174/how-do-i-compute-the-approximate-entropy-of-a-bit-string
Additional, potentially useful ideas from ChatGPT (interpreted by me):
- Entropy on event occurrence: for example a window-based approach checking frequencies of events.
- Inside of one event with multiple variables (entropy between words): is there a low entropy (always similar/same log) or high entropy (values are always different)
- Per variable: learn unigrams / n-grams of the values inside the values. But here you cannot simply learn the average or median over 1000 logs, because this loses rare events. You could however store all frequencies in the persistency (one per event) and then compare if the log matches any of the learned frequencies (within the threshold).
These are some ideas for future detectors that might be implemented.
https://stackoverflow.com/questions/2979174/how-do-i-compute-the-approximate-entropy-of-a-bit-string
Additional, potentially useful ideas from ChatGPT (interpreted by me):
These are some ideas for future detectors that might be implemented.