[Resource Topic] 2024/209: General Adversary Structures in Byzantine Agreement and Multi-Party Computation with Active and Omission Corruption

Welcome to the resource topic for 2024/209

Title:
General Adversary Structures in Byzantine Agreement and Multi-Party Computation with Active and Omission Corruption

Authors: Konstantinos Brazitikos, Vassilis Zikas

Abstract:

Typical results in multi-party computation (in short, MPC) capture faulty parties by assuming a threshold adversary corrupting parties actively and/or fail-corrupting. These corruption types are, however, inadequate for capturing correct parties that might suffer temporary network failures and/or localized faults - these are particularly relevant for MPC over large, global scale networks. Omission faults and general adversary structures have been proposed as more suitable alternatives. However, to date, there is no characterization of the feasibility landscape combining the above ramifications of fault types and patterns.
In this work we provide a tight characterization of feasibility of MPC in the presence of general adversaries - characterized by an adversary structure - that combine omission and active corruption. To this front we first provide a tight characterization of feasibility for Byzantine agreement (BA), a key tool in MPC protocols - this BA result can be of its own separate significance.
Subsequently, we demonstrate that the common techniques employed in the threshold MPC literature to deal with omission corruptions do not work in the general adversary setting, not even for proving bounds that would appear straightforward, e.g, sufficiency of the well known Q^3 condition on omission-only general adversaries. Nevertheless we provide a new protocol that implements general adversary MPC under a surprisingly complex, yet tight as we prove, bound.
As a contribution of independent interest, our work puts forth, for the first time, a formal treatment of general-adversary MPC with (active and) omission corruptions in Canettiā€™s universal composition framework.

ePrint: https://eprint.iacr.org/2024/209

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