Yotta: A Large-Scale Trustless Data Trading Scheme for Blockchain System

Liangxi Liu; Linshan Jiang; Mengyao Zheng; Xiang Liu; Yiming Qiu; Zhanpeng Guo

REVIEW 4 major objections 4 minor 28 references

Yotta: A Large-Scale Trustless Data Trading Scheme for Blockchain System

T0 review · 4 major / 4 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read Yotta claims 130x faster blockchain data trading with six properties

desk verdict Useful problem statement and a plausible combination of known pieces, but the security property fails on the protocol's own steps—the published key unlocks the IPFS address and the data is stored in the clear. read the letter →

arxiv 2506.19368 v1 pith:MR5ZWHA3 submitted 2025-06-24 cs.CR

Xiang Liu , Zhanpeng Guo , Liangxi Liu , Mengyao Zheng , Yiming Qiu , Linshan Jiang This is my paper · ORCID

classification cs.CR

keywords blockchaindatatradingWeb3.0IPFSzk-SNARKsmartcontracttrustlesssystemSQUATS

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper argues that no existing blockchain-based data-trading scheme can support large-scale, many-to-many exchanges while still protecting the data, and that the field has not even agreed on what properties such a scheme should have. It answers both gaps by proposing the SQUATS principles—Scalability, Quality, Usability, Autonomy, Transparency, Security—and then presenting Yotta, a batch trading protocol built on IPFS, smart contracts, and zk-SNARK proofs. In Yotta, each seller encrypts the IPFS address of their data, publishes a proof that the hidden data satisfies the buyer's stated quality function, and receives payment only after submitting a decryption key that the smart contract validates. The paper's central claim is that Yotta is the first complete scheme satisfying all SQUATS properties, with a prototype that outperforms the DCDH baseline by about 130 times at 10,000 sellers.

What carries the argument

The load-bearing object is the five-step Yotta workflow that couples address encryption with zk-SNARK provenance proofs and smart-contract key release. Its work is to decouple data possession and quality verification from key delivery: the seller proves possession and quality without revealing the data, while the blockchain handles payment deterministically only when the key decrypts the encrypted address correctly. Recursive SNARKs are the mechanism that lets one buyer verify many sellers' proofs in a single step, which is what converts one-to-many trades into many-to-many scale. The named property list SQUATS is the paper's own contribution as the formal target any large-scale trading scheme should satisfy.

What would settle it

Upload a plaintext dataset to IPFS, run the Yotta protocol with the address encrypted and the key published to the smart contract, and see whether an outside party who knows only the content address can retrieve the file; if they can, the claimed Security property fails.

Watch

Extended reading notes

Core claim

On the paper's own terms, Yotta is a trustless batch data-trading scheme for Web 3.0. Each seller stores their secret dataset on IPFS and encrypts only the IPFS address with a private key $K_i$, producing ciphertext $C_i$; the seller also uses zk-SNARK, a zero-knowledge proof with constant-size, data-independent verification, to demonstrate that the dataset satisfies the buyer's evaluation function $F()$, that $C_i$ really encrypts the address with $K_i$, and that $H(K_i)$ matches a published hash. The buyer verifies these proofs before depositing payment in a smart contract, and the contract pays each seller only if their submitted key decrypts $C_i$ to a valid address. The authors state that because only one of the key or the data is ever exposed and the data address is privately shared, the scheme achieves security along with scalability, making it a foundation for many-to-many data trading that no prior scheme has provided.

Load-bearing premise

The security property rests on the unstated assumption that files stored on IPFS cannot be fetched by anyone who knows their content address, because Yotta encrypts only the address and later releases the decryption key publicly for payment.

Editorial extensions

If this is right

If Yotta's claims hold, large-scale data markets can operate without a trusted escrow: buyers deposit in a smart contract and sellers are paid automatically for correct keys.
Buyers can verify data quality before payment because zk-SNARK proofs bind the buyer's evaluation function to the content-addressed data stored on IPFS.
The scheme's cost profile favors growth: the reported prototype goes from roughly 3x over DCDH at 10 users to 130x at 10,000 users, so gains increase with market size.
Recursive SNARK aggregation means the buyer's verification cost stays sublinear in the number of sellers, making many-to-many batches practical.
The SQUATS list gives later designs a concrete target to check against, potentially serving as a common benchmark for Web 3.0 data-trading proposals.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

If the IPFS access assumption is not guaranteed, Yotta's security property requires that the data payload itself be encrypted before upload; the paper only specifies encrypting the address, so a reader should not infer stronger confidentiality than the protocol text states.
The 130x figure compares a purpose-built prototype against a DCDH-based scheme; in a real deployment with network latency, storage costs, and on-chain gas fees, the relative gain could deviate, though the scaling trend should persist.
SQUATS could be applied as an evaluation checklist beyond Yotta, turning the paper's contribution from a single system into a standard that future schemes can be measured against.
A natural testable extension is to replace IPFS with other decentralized storage or add quality functions like Shapley values; the protocol's address-encryption structure is agnostic to that choice, per the paper's extensibility discussion.

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Signed reviews

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

Here's my take on Yotta. The paper puts its finger on a real problem—batch many-to-many data trading on blockchain with some verifiable quality guarantee—and the high-level architecture (IPFS for storage, zk-SNARKs for quality proof, smart-contract escrow for key exchange) is a sensible combination. That combination is genuinely new, as far as I can tell, even though each ingredient is standard. The SQUATS list is a reasonable checklist of desiderata. So the initial problem statement is worth a reader's time.

The problem is that the protocol doesn't actually do what it claims. Step 1 encrypts only the IPFS address with K_i; the data S_i goes to IPFS in the clear (the text says 'uploads their data to IPFS' without any encryption). Step 4 publishes all K_i on-chain. Since IPFS is content-addressed, anyone who sees the ledger can decrypt C_i, recover the address, and fetch the file. The Security bullet in Section 3.4 claims 'only the encryption key K_i is visible,' but that key is exactly what unlocks the address. Later, Section 3.5.1 says sellers encrypt their data on IPFS, but the protocol steps never generate or distribute a key for that payload, so the buyer couldn't decrypt it after the exchange. The paper is internally inconsistent: with plaintext IPFS objects, third parties get the data; with encrypted objects, the buyer can't. Either way, the 'complete scheme satisfying all six properties' claim is unsupported.

Beyond the security gap, there's no security proof, no adversarial model, no circuit description, and the evaluation is a simulation against an undescribed DCDH baseline with no code or parameters. The 130x speedup claim is not independently checkable. The SQUATS validation is a self-check against the paper's own checklist, which weakens the 'first to formalize' claim.

So the paper's real contribution is a clearly stated problem and a plausible architecture, not a working protocol. With a fix that actually encrypts the data and distributes the right keys, plus a real evaluation, it could be a worthwhile submission. As is, I wouldn't send it to a serious referee; desk reject is fair. If you see a revision that addresses the key-distribution problem and ships code, it's worth a second look.

Referee Report

4 major / 4 minor

Summary. The paper proposes Yotta, a blockchain-based batch data trading scheme combining IPFS, zk-SNARKs, and smart contracts. The authors introduce a set of six properties, SQUATS (Scalability, Quality, Usability, Autonomy, Transparency, Security), claim to be the first to formalize these requirements, and assert that Yotta satisfies all of them. A prototype simulation is reported to outperform a DCDH baseline by up to 130x at 10,000 sellers. The central claims are that Yotta is the first complete large-scale trustless data trading scheme and that it provides data security while supporting many-to-many transactions.

Significance. If the technical claims were correct, a batch data trading scheme with verifiable data quality and no trusted third party would be a meaningful contribution to blockchain-based data markets. The paper's five-step protocol is clearly presented, and the idea of using zk-SNARKs to bind a seller's data to an IPFS content hash and to the buyer's evaluation function is a sensible design goal. However, the paper provides no machine-checked proofs, no released code, no formal adversary model, and no reproducible experimental description. The central Security claim is contradicted by the protocol's own steps, and the performance evaluation is not independently checkable. For these reasons the claimed significance is not established.

major comments (4)

[Section 3.3.1, Steps 1(2)-(4), with Section 3.4 (Security)] The protocol does not protect the data payload. Step 1(3) uploads S_i to IPFS, Step 1(4) encrypts only address_i under K_i, and Step 4 publishes K_i on the smart contract. Once K_i is public, any party can decrypt C_i = Enc(K_i, address_i), obtain the IPFS content hash, and retrieve the plaintext file from IPFS. The alternative reading, suggested by Section 3.5.1's 'Encrypted Data Storage: Sellers encrypt their data and store them on IPFS', is that S_i itself is encrypted; but then the protocol never distributes the payload-decryption key to the buyer, so the buyer cannot access the purchased data. In either reading the Security property stated in Section 3.4, which promises that 'only the encryption key K_i is visible on the blockchain, preventing any third party from accessing the actual data content', is false, and the central claim that Yotta satisfies all six SQUATS properties is unsupported.
[Section 4 and Figure 2] The claimed up-to-130x speedup over the 'DCDH' baseline is not supported by any reproducible experimental description. The baseline is not defined or cited, no experimental setup or methodology is given, Figure 2 has no axis labels or units, and no error bars or repeated runs are reported. Since the baseline may itself implement the key-exchange approach criticized in Section 2.2, the comparison cannot validate scalability. The performance claim should be either removed or backed by a released prototype and a described baseline.
[Section 3.3.1, Step 1(6), with Section 3.4 (Quality)] The central quality guarantee rests on a zk-SNARK statement that the paper never instantiates. No circuit, proving key, verification key, or prover-cost measurement is provided for the claimed statement that S_i satisfies the buyer's evaluation function F(), that the committed data matches the IPFS content hash, and that C_i is an encryption of the address under K_i. Without a concrete circuit and cost analysis, the Quality property and the paper's scalability argument of constant proof size and verification cost are assertions, not results.
[Section 3.4 and Section 1] The SQUATS properties are introduced and evaluated by the same paper; the statement that Yotta 'satisfies all the essential properties' is established with informal prose bullets rather than formal definitions or independent verification. In particular, Scalability, Usability, and Autonomy are never given measurable criteria. As a result the paper's novelty claim of being the 'first' to formalize these requirements and to provide a 'complete' scheme is self-referential and cannot be checked by a reader. To make the claim meaningful, each property needs a formal definition and a method to test it.

minor comments (4)

[Figure 2 caption] The caption says 'DHDC' while the text and Section 4 refer to 'DCDH'; the two names should be reconciled.
[Notation, Sections 3.3.1 and 3.3.5] The paper uses 'address_i' in Step 1(4) and Step 5 but 'IPFS content hash H_ipfs_i' in Step 1(3) and Step 2; it should clarify that the encrypted value is the IPFS content hash or define the relation between the two notions.
[Page headers and footer] The running header contains 'Trovato et al.' and the footer contains 'Received 20 February 2007; revised 12 March 2009; accepted 5 June 2009', which are clearly template remnants and should be removed.
[Reference [12]] Reference [12] is a generic editorial introduction and does not support the claim that data trading is a key focus of Web 3.0; a more specific citation would be appropriate.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: Yotta's SQUATS checklist is self-authored but not tautological, the 130x comparison is an external (if underdescribed) baseline, and the security gap is a correctness flaw rather than a reduction to the paper's own inputs.

full rationale

I examined the claimed derivation chain: formalizing the SQUATS properties, designing Yotta to satisfy them, and evaluating against DCDH. The SQUATS properties are introduced by the same paper, but they are stated as general desiderata ('Scalability', 'Quality', 'Usability', 'Autonomy', 'Transparency', 'Security') and are not defined in terms of Yotta's specific mechanisms. Checking Yotta against them is design-to-spec, not a circular reduction in which the target conclusion is built into the premise. No fitted parameter is later renamed as a prediction: the reported up-to-130x result is a simulation comparison against a DCDH baseline; the baseline is underdescribed and the code is unreleased, which is a reproducibility problem, not circularity. I found no load-bearing self-citations: IPFS and zk-SNARK are cited to independent external references, and no uniqueness theorem from the authors is invoked to forbid alternatives. The apparent security contradiction (only the IPFS address is encrypted, yet the Security property claims third parties cannot access data content) is a serious correctness/design flaw, but it is an internal inconsistency rather than a circularity of the kind where the conclusion is equivalent to the inputs by construction. Accordingly, no specific circular step can be exhibited, and the circularity score is 0.

Assumptions & free parameters 0 free parameters · 4 assumptions · 0 invented entities

The paper introduces no new physical or cryptographic entities; its contributions are a protocol composition and a self-defined requirements checklist. The central claim rests on the unproved feasibility of the zk-SNARK steps and on an unstated data-confidentiality assumption for IPFS, both listed as axioms.

assumptions (4)

ad hoc to paper A zk-SNARK can be constructed that proves a seller possesses data S_i, that S_i satisfies the buyer's evaluation function F, that C_i encrypts the IPFS address under K_i, and that S_i matches the IPFS content hash, with practical prover cost.
Step 1(6) simply asserts such proofs are generated; no circuit, prover, or complexity analysis is provided, so the Quality and Scalability claims depend on this unproved capability.
domain assumption Data stored on IPFS is confidential as long as its content address (CID) is not published, and publishing the decryption key does not expose the data.
The protocol encrypts only the address (Step 1(4)) and later publishes K_i on-chain (Step 4); if IPFS content is fetchable by anyone with the CID, the Security property fails. There is no statement that the uploaded S_i is itself encrypted.
domain assumption Ethereum smart contracts can atomically verify submitted decryption keys against hashes and release or refund payments.
Steps 3-5 rely on on-chain key verification and conditional payment, but no gas costs or contract implementation details are given.
standard math Recursive zk-SNARKs can aggregate many sellers' proofs into a single buyer-side verification step.
The Scalability section references Halo Infinite for recursive SNARKs; this is an externally established result, but no implementation in Yotta is shown.

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Cite this review

Pith. "Pith review of Yotta: A Large-Scale Trustless Data Trading Scheme for Blockchain System." pith.science (2026). https://pith.science/paper/MR5ZWHA3

@misc{pith2026250619368,
  author       = {Pith},
  title        = {Pith review of: Yotta: A Large-Scale Trustless Data Trading Scheme for Blockchain System},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/MR5ZWHA3}},
  note         = {Machine review of arXiv:2506.19368}
}

read the original abstract

Data trading is one of the key focuses of Web 3.0. However, all the current methods that rely on blockchain-based smart contracts for data exchange cannot support large-scale data trading while ensuring data security, which falls short of fulfilling the spirit of Web 3.0. Even worse, there is currently a lack of discussion on the essential properties that large-scale data trading should satisfy. In this work, we are the first to formalize the property requirements for enabling data trading in Web 3.0. Based on these requirements, we are the first to propose Yotta, a complete batch data trading scheme for blockchain, which features a data trading design that leverages our innovative cryptographic workflow with IPFS and zk-SNARK. Our simulation results demonstrate that Yotta outperforms baseline approaches up to 130 times and exhibits excellent scalability to satisfy all the properties.

Figures

Figures reproduced from arXiv: 2506.19368 by the authors.

**Figure 2.** Our simulation experiments with Yotta scheme prototype and DHDC. [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗

Discussion (0). Continue with ORCID to comment.

Reference graph

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Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.

[1] [1]

Baoyi An, Mingjun Xiao, An Liu, Yun Xu, Xiangliang Zhang, and Qing Li. 2021. Secure crowdsensed data trading based on blockchain.IEEE Transactions on Mobile Computing22, 3 (2021), 1763–1778

work page 2021

[2] [2]

Juan Benet. 2014. Ipfs-content addressed, versioned, p2p file system.arXiv preprint arXiv:1407.3561(2014)

arXiv 2014

[3] [3]

Dan Boneh, Justin Drake, Ben Fisch, and Ariel Gabizon. 2020. Halo infinite: Recursive zk-SNARKs from any additive polynomial commitment scheme.Cryptology ePrint Archive(2020)

work page 2020

[4] [4]

Sean Bowe, Alessandro Chiesa, Matthew Green, Ian Miers, Pratyush Mishra, and Howard Wu. 2020. Zexe: Enabling decentralized private computation. In2020 IEEE Symposium on Security and Privacy (SP). IEEE, 947–964

work page 2020

[5] [5]

Binyi Chen, Benedikt Bünz, Dan Boneh, and Zhenfei Zhang. 2023. Hyperplonk: Plonk with linear-time prover and high-degree custom gates. In Annual International Conference on the Theory and Applications of Cryptographic Techniques. Springer, 499–530

work page 2023

[6] [6]

Fei Chen, Jiahao Wang, Changkun Jiang, Tao Xiang, and Yuanyuan Yang. 2022. Blockchain based non-repudiable iot data trading: Simpler, faster, and cheaper. InIEEE INFOCOM 2022-IEEE Conference on Computer Communications. IEEE, 1958–1967

work page 2022

[7] [7]

Weiqi Dai, Chunkai Dai, Kim-Kwang Raymond Choo, Changze Cui, Deiqing Zou, and Hai Jin. 2019. SDTE: A secure blockchain-based data trading ecosystem.IEEE Transactions on Information Forensics and Security15 (2019), 725–737

work page 2019

[8] [8]

Xiangqian Dong, Bing Guo, Yan Shen, Xuliang Duan, YC Shen, and H Zhang. 2018. An efficient and secure decentralizing data sharing model. Chinese Journal of Computers41, 5 (2018), 1021–1036

work page 2018