Abstract
Reputation is a major component of trustworthy systems. However, the subjective nature of reputation, makes it tricky to base a system’s security on it. In this work, we describe how to leverage reputation to establish a highly scalable and efficient blockchain. Our treatment puts emphasis on reputation fairness as a key feature of reputation-based protocols. We devise a definition of reputation fairness that ensures fair participation while giving chances to newly joining parties to participate and potentially build reputation. We also describe a concrete lottery in the random oracle model which achieves this definition of fairness. Our treatment of reputation-fairness can be of independent interest.
To avoid potential safety and/or liveness concerns stemming from the subjective and volatile nature of reputation, we propose a hybrid design that uses a Nakamoto-style ledger as a fallback. To our knowledge, our proposal is the first cryptographically secure design of a proof-of-reputation-based (in short PoR-based) blockchain that fortifies its PoR-based security by optimized Nakamoto-style consensus. This results in a ledger protocol which is provably secure if the reputation system is accurate, and preserves its basic safety properties even if it is not, as long as the fallback blockchain does not fail.
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- 1.
We do not specify here how this data is efficiently encoded into a block, e.g., so that they can be updated and addressed in an efficient manner; however, one can use the standard Merkle-tree approach used in many common blockchains, e.g., Bitcoin, Ethereum, Ouroboros, Algorand, etc.
- 2.
For instance, one can consider a mechanism which rewards honest behavior by increasing the parties’ reputation.
- 3.
- 4.
As a side note, our blockchain does address concerns about adaptivity in corruptions through its fallback mechanism, which can be adaptively secure.
- 5.
Observe that the adversary might send a message to a subset of parties, but if any honest party is instructed by the protocol to forward it, then the message will be delivered (to all other honest parties) in the round when this forwarding occurs.
- 6.
For notational simplicity, we often refer to \(\mathtt {Rep} \) as a probability distribution rather than an ensemble, i.e., we omit the explicit reference to the parameter m.
- 7.
Adaptive correlation-free reputation systems are described, analogously, as an ensemble of static reputation systems.
- 8.
All our security statements here involve a negligible probability of error. For brevity we at times omit this from the statement.
- 9.
The probability is taken over the coins associated with the distribution of the reputation system, and the coins of \(\mathcal {A}\) and \(\mathtt {A}\).
- 10.
This is analogous to the rankings of common reputation/recommendation systems, e.g., in Yelp, a party might have reputation represented by a number of stars from 0 to 5, along with their midpoints, i.e., 0.5, 1.5, 2.5, etc.
- 11.
This also gives us a way to effectively remove a reputation party—e.g., in case it is publicly caught cheating.
- 12.
In our blockchain construction, \(\textit{pid}\) will the P’s public key.
- 13.
In the random oracle model, r can be any unique nonce; however, for the epoch-resettable-adversary extension of our lottery we will need r to be a sufficiently fresh random value. Although most of our analysis here is in the static setting, we will still have r be such a random value to ensure compatibility with dynamic reputation.
- 14.
For clarity in our description we will use a deterministic broadcast protocol for \(\mathsf{Broadcast}\), e.g., the Dolev-Strong broadcast protocol [13] for which we know the exact number of rounds. However, since our lottery will ensure honest majority in \(\mathcal {C}_{\text {BA}}\), using the techniques by Cohen et al. [10, 11], we can replace the round-expensive Dolev-Strong broadcast protocol by an randomized, expected-constant round broadcast protocol for honest majorities, e.g., [19].
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Acknowledgements
This research was supported by Sunday Group, Inc. A full version of this work can be found on the Cryptology ePrint Archive [21]. The authors would like to thank Yehuda Afek for useful discussions.
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Kleinrock, L., Ostrovsky, R., Zikas, V. (2020). Proof-of-Reputation Blockchain with Nakamoto Fallback. In: Bhargavan, K., Oswald, E., Prabhakaran, M. (eds) Progress in Cryptology – INDOCRYPT 2020. INDOCRYPT 2020. Lecture Notes in Computer Science(), vol 12578. Springer, Cham. https://doi.org/10.1007/978-3-030-65277-7_2
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