Statistical Cryptography using a Fisher-Schr\"odinger Model
<|reference_start|>Statistical Cryptography using a Fisher-Schr\"odinger Model: A principled procedure to infer a hierarchy of statistical distributions possessing ill-conditioned eigenstructures, from incomplete constraints, is presented. The inference process of the \textit{pdf}'s employs the Fisher information as the measure of uncertainty, and, utilizes a semi-supervised learning paradigm based on a measurement-response model. The principle underlying the learning paradigm involves providing a quantum mechanical connotation to statistical processes. The inferred \textit{pdf}'s constitute a statistical host that facilitates the encryption/decryption of covert information (code). A systematic strategy to encrypt/decrypt code via unitary projections into the \textit{null spaces} of the ill-conditioned eigenstructures, is presented. Numerical simulations exemplify the efficacy of the model.<|reference_end|>
@article{venkatesan2007statistical,
    title={Statistical Cryptography using a Fisher-Schr\"{o}dinger Model},
    author={R. C. Venkatesan},
    journal={arXiv preprint arXiv:cond-mat/0701319},
    year={2007},
    archivePrefix={arXiv},
    eprint={cond-mat/0701319},
    primaryClass={cond-mat.stat-mech cs.CR}
}