[Resource Topic] 2024/729: Covert Adaptive Adversary Model: A New Adversary Model for Multiparty Computation

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Covert Adaptive Adversary Model: A New Adversary Model for Multiparty Computation

Authors: Isheeta Nargis, Anwar Hasan


In covert adversary model, the corrupted parties can behave in any possible way like active adversaries, but any party that attempts to cheat is guaranteed to get caught by the honest parties with a minimum fixed probability. That probability is called the deterrence factor of covert adversary model. Security-wise, covert adversary is stronger than passive adversary and weaker than active adversary. It is more realistic than passive adversary model. Protocols for covert adversaries are significantly more efficient than protocols for active adversaries. Covert adversary model is defined only for static corruption. Adaptive adversary model is more realistic than static adversaries. In this article, we define a new adversary model, the covert adaptive adversary model, by generalizing the definition of covert adversary model for the more realistic adaptive corruption. We prove security relations between the new covert adaptive adversary model with existing adversary models like passive adaptive adversary model, active adaptive
adversary model and covert static adversary model. We prove the sequential composition theorem for the new adversary model which is necessary to allow modular design of protocols for this new adversary model.

ePrint: https://eprint.iacr.org/2024/729

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