We propose a novel distributed monetary system called Hearsay that tolerates both Byzantine and rational behavior without the need for agents to reach consensus on executed transactions. Recent work [5,10,15] has shown that distributed monetary systems do not require consensus and can operate using a broadcast primitive with weaker guarantees, such as reliable broadcast. However, these protocols assume that some number of agents may be Byzantine and the remaining agents are perfectly correct. For the application of a monetary system in which the agents are real people with economic interests, the assumption that agents are perfectly correct may be too strong. We expand upon this line of thought by weakening the assumption of correctness and instead adopting a fault tolerance model which allows up to < 3 agents to be Byzantine and the remaining agents to be rational. A rational agent is one which will deviate from the protocol if it is in their own best interest. Under this fault tolerance model, Hearsay implements a monetary system in which all rational agents achieve agreement on executed transactions. Moreover, Hearsay requires only a single broadcast per transaction. In order to incentivize rational agents to behave correctly in Hearsay, agents are rewarded with transaction fees for participation in the protocol and punished for noticeable deviations from the protocol. Additionally, Hearsay uses a novel broadcast primitive called Rational Reliable Broadcast to ensure that agents can broadcast messages under Hearsay's fault tolerance model. Rational Reliable Broadcast achieves equivalent guarantees to Byzantine Reliable Broadcast [7] but can tolerate the presence of rational agents. To show this, we prove that following the Rational Reliable Broadcast protocol constitutes a Nash equilibrium between rational agents. We deem Rational Reliable Broadcast to be a secondary contribution of this work which may be of independent interest.
Over the past five years, the rewards associated with mining Proof-of-Work blockchains have increased substantially. As a result, miners are heavily incentivized to design and utilize Application Specific Integrated Circuits (ASICs) that can compute hashes far more efficiently than existing general purpose hardware. Currently, it is difficult for most users to purchase and operate ASICs due to pricing and availability constraints, resulting in a relatively small number of miners with respect to total user base for most popular cryptocurrencies. In this work, we aim to invert the problem of ASIC development by constructing a Proof-of-Work function for which an existing general purpose processor (GPP, such as an x86 IC) is already an optimized ASIC. In doing so, we will ensure that any would-be miner either already owns an ASIC for the Proof-of-Work system they wish to participate in or can attain one at a competitive price with relative ease. In order to achieve this, we present HashCore, a Proof-of-Work function composed of "widgets" generated pseudo-randomly at runtime that each execute a sequence of general purpose processor instructions designed to stress the computational resources of such a GPP. The widgets will be modeled after workloads that GPPs have been optimized for, for example, the SPEC CPU 2017 benchmark suite for x86 ICs, in a technique we refer to as inverted benchmarking. We provide a proof that HashCore is collision-resistant regardless of how the widgets are implemented. We observe that GPP designers/developers essentially create an ASIC for benchmarks such as SPEC CPU 2017. By modeling HashCore after such benchmarks, we create a Proof-of-Work function that can be run most efficiently on a GPP, resulting in a more accessible, competitive, and balanced mining market.
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