Cryptology ePrint Archive: Report 2021/775

Adaptively Secure Broadcast in Resource-Restricted Cryptography

Ran Cohen and Juan Garay and Vassilis Zikas

Abstract: The advent of blockchain protocols has reignited the interest in adaptively secure broadcast, as it is by now well known that broadcasting over a diffusion network allows an adaptive adversary to corrupt the sender depending on the message s/he attempts to send and change it. Hirt and Zikas [Eurocrypt '10] proved that this is an inherent limitation of broadcast in the simulation-based setting, i.e., that this task is impossible against an adaptive adversary corrupting a strict majority of the parties.

In this work, we show that, contrary to previous perception, the above limitation is not an artifact of simulation-based security, but that it also applies to the property-based broadcast definition adapted for adaptive adversaries. We then turn to the resource-restricting cryptography (RRC) paradigm, which was proven useful in circumventing strong impossibility results, and ask whether it also allows us to circumvent the above negative result. We answer this question in the affirmative, by showing that time-lock puzzles (TLPs)---which can be viewed as an instance of RRC---indeed allow for achieving the property-based definition and circumvent the impossibility of adaptively secure broadcast.

The natural question is then, do TLPs also allow for simulation-based adaptively secure broadcast against corrupted majorities? It turns out that they do not, which serves as yet another motivation for simulation-based security, especially when dealing with adaptive adversaries. Nonetheless, we show that a positive result can be achieved if we turn to what is essentially a non-committing version of TLPs, which uses access to a programmable random oracle.

Category / Keywords: cryptographic protocols / Broadcast, adaptive security, cryptographic protocols

Date: received 8 Jun 2021

Contact author: rancohen at ccs neu edu, garay at cse tamu edu, vzikas at cs purdue edu

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Version: 20210609:063121 (All versions of this report)

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