Aggregatable Subvector Commitments for Stateless Cryptocurrencies

An aggregatable subvector commitment (aSVC) scheme is a vector commitment (VC) scheme that can aggregate multiple proofs into a single, small subvector proof. In this paper, we formalize aSVCs and give a construction from constant-sized polynomial commitments. Our construction is unique in that it has linear-sized public parameters, it can compute all constant-sized proofs in quasilinear time, it updates proofs in constant time and it can aggregate multiple proofs into a constant-sized subvector proof. Furthermore, our concrete proof sizes are small due to our use of pairing-friendly groups. We use our aSVC to obtain a payments-only stateless cryptocurrency with very low communication and computation overheads. Specifically, our constant-sized, aggregatable proofs reduce each block’s proof overhead to a single group element, which is optimal. Furthermore, our subvector proofs speed up block verification and our smaller public parameters further reduce block size

BalanceProofs: Maintainable Vector Commitments with Fast Aggregation

We present BalanceProofs, the first vector commitment that is maintainable (i.e., supporting sublinear updates) while also enjoying fast proof aggregation and verification. The basic version of BalanceProofs has $O(\sqrt{n}\log n)$ update time and $O(\sqrt{n})$ query time and its constant-size aggregated proofs can be produced and verified in milliseconds. In particular, BalanceProofs improves the aggregation time and aggregation verification time of the only known maintainable and aggregatable vector commitment scheme, Hyperproofs (USENIX SECURITY 2022), by up to 1000$\times$ and up to 100$\times$ respectively. Fast verification of aggregated proofs is particularly useful for applications such as stateless cryptocurrencies (and was a major bottleneck for Hyperproofs), where an aggregated proof of balances is produced once but must be verified multiple times and by a large number of nodes. As a limitation, the updating time in BalanceProofs compared to Hyperproofs is roughly $6\times$ slower, but always stays in the range from 10 to 18 milliseconds. We finally study useful tradeoffs in BalanceProofs between (aggregate) proof size, update time and (aggregate) proof computation and verification, by introducing a bucketing technique, and present an extensive evaluation as well as a comparison to Hyperproofs

Pointproofs: Aggregating Proofs for Multiple Vector Commitments

Vector commitments enable a user to commit to a sequence of values and provably reveal one or many values at specific positions at a later time. In this work, we construct Pointproofs--a new vector commitment scheme that supports non-interactive aggregation of proofs across multiple commitments. Our construction enables any third party to aggregate a collection of proofs with respect to different, independently computed commitments into a single proof represented by an elliptic curve point of 48-bytes. In addition, our scheme is hiding: a commitment and proofs for some values reveal no information about the remaining values. We build Pointproofs and demonstrate how to apply them to blockchain smart contracts. In our example application, Pointproofs reduce bandwidth overheads for propagating a block of transactions by at least 60% compared to prior state-of-art vector commitments. Pointproofs are also efficient: on a single-thread, it takes 0.08 seconds to generate a proof for 8 values with respect to one commitment, 0.25 seconds to aggregate 4000 such proofs across multiple commitments into one proof, and 23 seconds (0.7 ms per value proven) to verify the aggregated proof

Linear-map Vector Commitments and their Practical Applications

Vector commitments (VC) are a cryptographic primitive that allow one to commit to a vector and then “open” some of its positions efficiently. Vector commitments are increasingly recognized as a central tool to scale highly decentralized networks of large size and whose content is dynamic. In this work, we examine the demands on the properties that an ideal vector commitment should satisfy in the light of the emerging plethora of practical applications and propose new constructions that improve the state-of-the-art in several dimensions and offer new tradeoffs. We also propose a unifying framework that captures several constructions and show how to generically achieve some properties from more basic ones. On the practical side, we focus on building efficient schemes that do not require new trusted setup (we can reuse existing ceremonies for pairing-based “powers of tau” run by real-world systems such as ZCash or Filecoin). Our (in-progress) implementation demonstrates that our work over-performs in efficiency prior schemes with same properties

Succinct Vector, Polynomial, and Functional Commitments from Lattices

Vector commitment schemes allow a user to commit to a vector of values $\mathbf{x} \in \{0,1\}^\ell$ and later, open up the commitment to a specific set of positions. Both the size of the commitment and the size of the opening should be succinct (i.e., polylogarithmic in the length $\ell$ of the vector). Vector commitments and their generalizations to polynomial commitments and functional commitments are key building blocks for many cryptographic protocols. We introduce a new framework for constructing non-interactive lattice-based vector commitments and their generalizations. A simple instantiation of our framework yields a new vector commitment scheme from the standard short integer solution (SIS) assumption that supports private openings and large messages. We then show how to use our framework to obtain the first succinct functional commitment scheme that supports openings with respect to arbitrary bounded-depth Boolean circuits. In this scheme, a user commits to a vector $\mathbf{x} \in \{0,1\}^\ell$, and later on, open the commitment to any function $f(\mathbf{x})$. Both the commitment and the opening are non-interactive and succinct: namely, they have size $\textsf{poly}(\lambda, d, \log \ell)$, where $\lambda$ is the security parameter and $d$ is the depth of the Boolean circuit computing $f$. Previous constructions of functional commitments could only support constant-degree polynomials, or require a trusted online authority, or rely on non-falsifiable assumptions. The security of our functional commitment scheme is based on a new falsifiable family of basis-augmented SIS assumptions (BASIS) we introduce in this work. We also show how to use our vector commitment framework to obtain (1) a polynomial commitment scheme where the user can commit to a polynomial $f \in \mathbb{Z}_q[x]$ and subsequently open the commitment to an evaluation $f(x) \in \mathbb{Z}_q$; and (2) an aggregatable vector (resp., functional) commitment where a user can take a set of openings to multiple indices (resp., function evaluations) and aggregate them into a single short opening. Both of these extensions rely on the same BASIS assumption we use to obtain our succinct functional commitment scheme

SoK: Blockchain Light Clients

Blockchain systems, as append-only ledgers, are typically associated with linearly growing participation costs. Therefore, for a blockchain client to interact with the system (query or submit a transaction), it can either pay these costs by downloading, storing and verifying the blockchain history, or forfeit blockchain security guarantees and place its trust on third party intermediary servers. With this problem becoming apparent from early works in the blockchain space, the concept of a light client has been proposed, where a resource-constrained client such as a browser or mobile device can participate in the system by querying and/or submitting transactions without holding the full blockchain but while still inheriting the blockchain\u27s security guarantees. A plethora of blockchain systems with different light client frameworks and implementations have been proposed, each with different functionalities, assumptions and efficiencies. In this work we provide a systematization of such light client designs. We unify the space by providing a set of definitions on their properties in terms of provided functionality, efficiency and security, and provide future research directions based on our findings

Vector and Functional Commitments from Lattices

Vector commitment (VC) schemes allow one to commit concisely to an ordered sequence of values, so that the values at desired positions can later be proved concisely. In addition, a VC can be statelessly updatable, meaning that commitments and proofs can be updated to reflect changes to individual entries, using knowledge of just those changes (and not the entire vector). VCs have found important applications in verifiable outsourced databases, cryptographic accumulators, and cryptocurrencies. However, to date there have been relatively few post-quantum constructions, i.e., ones that are plausibly secure against quantum attacks. More generally, functional commitment (FC) schemes allow one to concisely and verifiably reveal various functions of committed data, such as linear functions (i.e., inner products, including evaluations of a committed polynomial). Under falsifiable assumptions, all known functional commitments schemes have been limited to ``linearizable\u27\u27 functions, and there are no known post-quantum FC schemes beyond ordinary VCs. In this work we give post-quantum constructions of vector and functional commitments based on the standard Short Integer Solution lattice problem (appropriately parameterized): \begin{itemize} \item First, we present new statelessly updatable VCs with significantly shorter proofs than (and efficiency otherwise similar to) the only prior post-quantum, statelessly updatable construction (Papamanthou \etal, EUROCRYPT 13). Our constructions use private-key setup, in which an authority generates public parameters and then goes offline. \item Second, we construct functional commitments for \emph{arbitrary (bounded) Boolean circuits} and branching programs. Under falsifiable assumptions, this is the first post-quantum FC scheme beyond ordinary VCs, and the first FC scheme of any kind that goes beyond linearizable functions. Our construction works in a new model involving an authority that generates the public parameters and remains online to provide public, reusable ``opening keys\u27\u27 for desired functions of committed messages. \end{itemize

Limits on revocable proof systems, with applications to stateless blockchains

Motivated by the goal of building a cryptocurrency with succinct global state, we introduce the abstract notion of a revocable proof system. We prove an information-theoretic result on the relation between global state size and the required number of local proof updates as statements are revoked (e.g., coins are spent). We apply our result to conclude that there is no useful trade-off point when building a stateless cryptocurrency: the system must either have a linear-sized global state (in the number of accounts in the system) or require a near-linear rate of local proof updates. The notion of a revocable proof system is quite general and also provides new lower bounds for set commitments, vector commitments and authenticated dictionaries

Edrax: A Cryptocurrency with Stateless Transaction Validation

We present EDRAX, an architecture for cryptocurrencies with stateless transaction validation. In EDRAX, miners and validating nodes process transactions and blocks simply by accessing a short commitment of the current state found in the most recent block. Therefore there is no need to store off-chain and on-disk, order-of-gigabytes large validation state. We present two instantiations of EDRAX, one in the UTXO model and one in the accounts model. Our UTXO instantiation uses sparse Merkle trees, which are very fast and require no trusted setup. Our accounts instantiation uses a distributed vector commitment, a type of vector commitment that has state-independent updates, meaning it can be synchronized by accessing only update data (e.g., send 5 ETH from Alice to Bob). Towards this goal, we build a new succinct distributed vector commitment based on multiplexer polynomials and zk-SNARKs, that scales up to one billion accounts. We perform an extensive experimental evaluation comparing to other (recently) proposed approaches for stateless transaction validation, showing that sparse Merkle trees and our new distributed vector commitment offer excellent tradeoffs in this application domain

Incrementally Aggregatable Vector Commitments and Applications to Verifiable Decentralized Storage

Vector commitments with subvector openings (SVC) [Lai-Malavolta, Boneh-Bunz-Fisch; CRYPTO\u2719] allow one to open a committed vector at a set of positions with an opening of size independent of both the vector\u27s length and the number of opened positions. We continue the study of SVC with two goals in mind: improving their efficiency and making them more suitable to decentralized settings. We address both problems by proposing a new notion for VC that we call incremental aggregation and that allows one to merge openings in a succinct way an unbounded number of times. We show two applications of this property. The first one is immediate and is a method to generate openings in a distributed way. For the second one, we use incremental aggregation to design an algorithm for faster generation of openings via preprocessing. We then proceed to realize SVC with incremental aggregation. We provide two constructions in groups of unknown order that, similarly to that of Boneh et al. (which supports only one-hop aggregation), have constant-size public parameters, commitments and openings. As an additional feature, for the first construction we propose efficient arguments of knowledge of subvector openings which immediately yields a keyless proof of storage with compact proofs. Finally, we address a problem closely related to that of SVC: storing a file efficiently in completely decentralized networks. We introduce and construct verifiable decentralized storage (VDS), a cryptographic primitive that allows to check the integrity of a file stored by a network of nodes in a distributed and decentralized way. Our VDS constructions rely on our new vector commitment techniques