Multiparty Computation with Low Communication, Computation and Interaction via Threshold FHE

By Gilad Asharov, Abhishek Jain, Adriana López-Alt, Eran Tromer, Vinod Vaikuntanathan, Daniel Wichs. International Conference on the Theory and Application of Cryptographic Techniques, 2012

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Simple Encrypted Arithmetic Library - SEAL v2.1 (2016, methodology): “[4]) can be used together with the heuristic noise growth estimates implemented in SEAL v2.”
Multiparty Computation from Somewhat Homomorphic Encryption (2012, background): “In recent independent work [24, 2, 16], Meyers at al.”
A Pragmatic Introduction to Secure Multi-Party Computation (2019, background): “Since the work of Aumann and Lindell (2007), significant progress in efficient OT has produced several extremely efficient malicious OT protocols (Asharov et al.”
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications (2018, background): “, [5]) or extending Yao’s garbled circuit protocol (e.”
Fast Private Set Intersection from Homomorphic Encryption (2017, background): “[5]) implies that in order to achieve 2−λ statistical distance between output ciphertexts of different executions, it suffices to add encryptions of zero with noise λ + log2 n + log2 α bits larger than an upper bound on the noise in the original outputs of the computation.”
Simple Encrypted Arithmetic Library v2.3.0 (2017, methodology): “[3]) can be used together with the heuristic noise growth estimates implemented in SEAL v2.”
GGHLite: More Efficient Multilinear Maps from Ideal Lattices (2014, methodology): “This technique, also called “smudging,”was previously used in other applications [3,10,2,4].”