Jack Doerner

TL;DR: A hybrid multi-party computation protocol that combines Yao’s garbled circuits with tailored protocols for computing inner products is proposed, suitable for secure computation because it uses an efficient fixed-point representation of real numbers while maintaining accuracy and convergence rates comparable to what can be obtained with a classical solution using floating point numbers.

TL;DR: This work designs and implements a Distributed Oblivious Random Access Memory (DORAM) data structure that is optimized for use in two-party secure computation protocols, and finds that it still outperforms the fastest previously known constructions, Circuit ORAM and Square-root ORAM, for datasets that are 32 KiB or larger.

TL;DR: This work proposes new protocols for multi-party ECDSA key-generation and signing with a threshold of two, which prove secure against malicious adversaries in the random oracle model using only the Computational Diffie-Hellman Assumption and the assumptions already implied by E CDSA itself.

TL;DR: This work shows how the classical square-root ORAM of Goldreich and Ostrovsky can be modified to overcome asymptotically worse than the best known schemes, and shows a design that has over 100x lower initialization cost, and provides benefits over linear scan for just 8 blocks of data.

TL;DR: The solution enables organizations to collaborate in the construction of a predictive model while keeping their training data private and leads to highly scalable solutions that can solve data analysis problems with one million records and one hundred features in less than one hour.