Week 9: The Oracle of Entropy

Welcome back to my blog! I have continued my Literature Review and have also reviewed my GitHub repository. However, I have come up with the idea of creating a virtual machine that checks whether a key has truly passed randomness. I call it the ‘Oracle of Entropy’, and it is a useful addition to my project. 

It generates binary cryptographic keys using Python, and these keys can be GAN-generated. It converts them into a raw binary format that is suitable for low-level analysis, since the C language is seen by many as “low-level”, meaning that it works far more actively with the memory and hardware architecture compared to higher-level languages, such as Python for instance. The analysis system then analyzes the entropy of each key in C using Shannon entropy, a very efficient way to judge the randomness. After parsing, each key receives symbolic names. 

My “oracle of entropy” folder consists of a generator, analyzer, interpreter, interface (between Python and C), keys (that store generated .npy and .bin keys), and outputs. So, the final output is a JSON object that contains the entropy, verdict, symbol, poetic name, timestamp, and the hash value. Out of the maximum entropy of 8.0000, my entropy value of 7.9986 is extremely high. So, the key is very random and cryptographically strong. For security reasons, I will not give out the actual hash value here, but anyone with the hash can verify the key’s identity. Here’s an example output:

{

  “entropy”: 7.9986,

  “verdict”: “Sacred”,

  “symbol”: “🜄”,

  “name”: “Silent Tongue”,

  “timestamp”: “2099-07-11 12:36:25”,

  “sha256”: “870bfce9…”

}

The machine treats entropy as an important and poetic process, which I find to be a fascinating addition to this project. I hope you all enjoyed the blog and see you next week!