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2019 | OriginalPaper | Buchkapitel

Cryptographic Sensing

verfasst von : Yuval Ishai, Eyal Kushilevitz, Rafail Ostrovsky, Amit Sahai

Erschienen in: Advances in Cryptology – CRYPTO 2019

Verlag: Springer International Publishing

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Abstract

Is it possible to measure a physical object in a way that makes the measurement signals unintelligible to an external observer? Alternatively, can one learn a natural concept by using a contrived training set that makes the labeled examples useless without the line of thought that has led to their choice? We initiate a study of “cryptographic sensing” problems of this type, presenting definitions, positive and negative results, and directions for further research.

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Fußnoten
1
The requirement that \(b<1\) is what rules out the trivial solution where h is just the list of labels for the m points in S and forces actual “learning”.
 
2
In the case of proper PAC-learning (i.e., when \(\mathcal{H}=\mathcal{F}\)), [18] present a condition (called “closure under exception lists”) on \(\mathcal{F}\) under which PAC still implies OCCAM learning.
 
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Metadaten
Titel
Cryptographic Sensing
verfasst von
Yuval Ishai
Eyal Kushilevitz
Rafail Ostrovsky
Amit Sahai
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-26954-8_19