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This paper presents the first provably secure localization method for smart automotive systems. Using this method, a lost car can compute its location with assistance from three nearby cars while the locations of all the participating cars including the lost car remain private. This localization application is one of the very first location-based services that does not sacrifice accuracy to maintain...
We introduce Tiny Garble, a novel automated methodology based on powerful logic synthesis techniques for generating and optimizing compressed Boolean circuits used in secure computation, such as Yao's Garbled Circuit (GC) protocol. Tiny Garble achieves an unprecedented level of compactness and scalability by using a sequential circuit description for GC. We introduce new libraries and transformations,...
This paper introduces the first efficient, scalable, and practical method for privacy-preserving k-nearest neighbors (k-NN) search. The approach enables performing the widely used k-NN search in sensitive scenarios where none of the parties reveal their information while they can still cooperatively find the nearest matches. The privacy preservation is based on the Yao's garbled circuit (GC) protocol...
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