Monday, October 19, 2020
Can we measure a physical object in a way that makes the measurement signals unintelligible to an external observer? Can we 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.
Joint work with Eyal Kushilevitz, Rafail Ostrovsky, and Amit Sahai
Yuval Ishai is a professor of Computer Science at the Technion, Israel. He is mainly working in the area of cryptography, but is broadly interested in theoretical computer science. He published more than 150 research papers that were recognized by best paper awards at the FOCS 2004, Crypto 2007, and Crypto 2016 conferences and by a SIAM Outstanding Paper Prize. He was inducted as an IACR Fellow in 2018.