We present Catena, an efficiently-verifiable Bitcoin witnessing scheme. Catena enables any number of thin clients, such as mobile phones, to efficiently agree on a log of applicationspecific statements managed by an adversarial server. Catena implements a log as an OP_RETURN transaction chain and prevents forks in the log by leveraging Bitcoin's security against double spends. Specifically, if a log server wants to equivocate it has to double spend a Bitcoin transaction output. Thus, Catena logs are as hard to fork as the Bitcoin blockchain: an adversary without a large fraction of the network's computational power cannot fork Bitcoin and thus cannot fork a Catena log either. However, different from previous Bitcoin-based work, Catena decreases the bandwidth requirements of log auditors from 90 GB to only tens of megabytes. More precisely, our clients only need to download all Bitcoin block headers (currently less than 35 MB) and a small, 600-byte proof for each statement in a block. We implement Catena in Java using the bitcoinj library and use it to extend CONIKS, a recent key transparency scheme, to witness its public-key directory in the Bitcoin blockchain where it can be efficiently verified by auditors. We show that Catena can secure many systems today, such as public-key directories, Tor directory servers and software transparency schemes.
We give a protocol for Asynchronous Distributed Key Generation (A-DKG) that is optimally resilient (can withstand < 3 faulty parties), has a constant expected number of rounds, has˜( 3 ) expected communication complexity, and assumes only the existence of a PKI. Prior to our work, the best A-DKG protocols required Ω( ) expected number of rounds, and Ω( 4 ) expected communication.Our A-DKG protocol relies on several building blocks that are of independent interest. We define and design a Proposal Election (PE) protocol that allows parties to retrospectively agree on a valid proposal after enough proposals have been sent from different parties.With constant probability the elected proposal was proposed by a nonfaulty party. In building our PE protocol, we design a Verifiable Gather protocol which allows parties to communicate which proposals they have and have not seen in a verifiable manner. The final building block to our A-DKG is a Validated Asynchronous Byzantine Agreement (VABA) protocol. We use our PE protocol to construct a VABA protocol that does not require leaders or an asynchronous DKG setup. Our VABA protocol can be used more generally when it is not possible to use threshold signatures. CCS CONCEPTS• Theory of computation → Distributed algorithms; Cryptographic protocols.
In this paper, we introduce a distributed key generation (DKG) protocol with aggregatable and publicly-verifiable transcripts. Compared with prior publicly-verifiable approaches, our DKG reduces the size of the final transcript and the time to verify it from O(n 2 ) to O(n log n), where n denotes the number of parties. As compared with prior non-publicly-verifiable approaches, our DKG leverages gossip rather than all-to-all communication to reduce verification and communication complexity. We also revisit existing DKG security definitions, which are quite strong, and propose new and natural relaxations. As a result, we can prove the security of our aggregatable DKG as well as that of several existing DKGs, including the popular Pedersen variant. We show that, under these new definitions, these existing DKGs can be used to yield secure threshold variants of popular cryptosystems such as El-Gamal encryption and BLS signatures. We also prove that our DKG can be securely combined with a new efficient verifiable unpredictable function (VUF), whose security we prove in the random oracle model. Finally, we experimentally evaluate our DKG and show that the perparty overheads scale linearly and are practical. For 64 parties, it takes 71 ms to share and 359 ms to verify the overall transcript, while for 8192 parties, it takes 8 s and 42.2 s respectively. cLabs, Ethereum Foundation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.