We investigate the extraction of cryptographic keying material from nano-scale variations of digital circuit outputs by using nested polar codes and neural leakage estimators. A runtime-efficient algorithm is developed to simulate such a system. A certain family of digital circuit outputs are known to be a source of randomness that can be used as a unique identifier for each output. By generating secret keys from these unique outputs, one can apply cryptographic methods by using the secret keys as the seed. One is required to store extra helper data generated first time the outputs are measured, since there is noise in digital circuit outputs, to be able to reconstruct the same key from every measurement of the same digital circuit. The generation of the secret keys and helper data follow a nested polar code construction, and they are generated in this thesis to estimate the Shannon entropy of the secret key and secrecy leakage to a passive attacker using neural networks. The estimators used illustrate, for the first time, that the system generates secret keys of almost maximum entropy and negligible secrecy leakage for practical cryptographic systems if the digital circuit outputs can be preprocessed to obtain almost independent and identically distributed (i.i.d.) random outputs distributed according to a binary uniform distribution. The algorithm design is evaluated and improvements for lower runtime are suggested. Ideas for future research are presented.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-204515 |
| Date | January 2024 |
| Creators | Bergström, Didrik |
| Publisher | Linköpings universitet, Institutionen för systemteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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