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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CITATION STYLE
Ishai, Y., Kushilevitz, E., Ostrovsky, R., & Sahai, A. (2019). Cryptographic Sensing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11694 LNCS, pp. 583–604). Springer Verlag. https://doi.org/10.1007/978-3-030-26954-8_19
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