Efficient, Oblivious Data Structures for MPC

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Privacy-Preserving Distributed Linear Regression on High-Dimensional Data (2017, methodology): “Popular applications used for the empirical evaluation of practical MPC systems include graph algorithms [5, 32, 42, 51, 57], data structure algorithms [42, 51], string matching and distance algorithms [36, 37, 66] and AES [3, 36, 37, 66].”
A Pragmatic Introduction to Secure Multi-Party Computation (2019, background): “(Keller and Scholl, 2014) proposed e cient MPC data structures for arrays, built on top of ORAM designs.”
Secure Linear Regression on Vertically Partitioned Datasets (2016, methodology): “Popular applications used for the empirical evaluation of implemented systems include graph algorithms [6, 18, 24, 29, 34, 45], data structure algorithms [24,29,42], string matching and distance algorithms [20,21,39] and AES [4,20,21,39].”
Path ORAM: an extremely simple oblivious RAM protocol (2012, unknown): “We ﬁrst describe the Path ORAM protocol with N/χ + O (log N ) · ω (1) blocks of client storage, and then later in Section 3.7 we explain how the client storage can be reduced to O (log 2 N/ log χ ) · ω (1) blocks via recursion.”
Circuit ORAM: On Tightness of the Goldreich-Ostrovsky Lower Bound (2015, background): “(1) 0.97M Table 1: Circuit size of various ORAM schemes.”
MP-SPDZ: A Versatile Framework for Multi-Party Computation (2020, methodology): “MP-SPDZ retains the code used by Keller and Scholl [52].”