Literature Survey: Blockchain Zero Knowledge

Domain: Cybersecurity & Applied Cryptography
Topic Search: blockchain zero knowledge
Timeframe: 2021 - 2026

This is a curated survey of recent publications focusing on blockchain zero knowledge. Results are filtered for top-tier journals and prominent conferences.

📚 Curated Peer-Reviewed Publications

1. DART: Distributed Zero Knowledge Data Auditing With Retrievability for Blockchain-Based Decentralized Storage Networks

Venue: TIFS | Year: 2025 | Citations: 3 Authors: Haiyang Yu 0001, Yurun Chen 0002, Shen Su, Jian Su 0001, Yuwen Chen 0002 et al.

The advent of blockchain technology has led to the development of decentralized storage networks, revolutionizing the way data are stored and accessed and offering advantages such as cost-effective services, improved data sovereignty, and resistance to censorship. However, nodes of decentralized storage networks cannot be fully trusted and data stored in them may not be as secure and intact as claimed. Therefore, how to guarantee the storage service quality in decentralized storage networks is still a major problem to be solved. In this paper, we propose DART, a distributed zero knowledge data auditing scheme for blockchain-based decentralized storage networks, periodically authenticating both the integrity and the retrievability of data in decentralized storage networks. We design an efficient integrity auditing protocol for decentralized nodes based on distributed zero knowledge protocols, which improves the performance of auditing whilst maintaining low cost with zero knowledge protocols. Furthermore, we introduce the erasure code in decentralized storage networks to support data retrievability across decentralized nodes. By leveraging accumulator techniques to design a dual accumulation strategy, we build a batch verification approach to improve the communication and computation efficiency in data retrieval checking. We analyze the security of DART under the random oracle model and conduct extensive experiments to evaluate its performance. Experimental results affirm that DART outperforms state-of-the-art approaches in decentralized storage networks, reducing the overhead in both the storage and verification phases by more than 70%. Moreover, this performance advantage becomes increasingly pronounced with larger file sizes, underscoring the scalability and practicality of DART.

2. VeRange: Verification-efficient Zero-knowledge Range Arguments with Transparent Setup for Blockchain Applications and More

Venue: ASIACCS | Year: 2025 | Citations: 1 Authors: Yue Zhou, Sid Chi-Kin Chau

Zero-knowledge range arguments are a fundamental cryptographic primitive that allows a prover to convince a verifier of the knowledge of a secret value lying within a predefined range. They have been utilized in diverse applications, such as confidential transactions. Range arguments with a transparent setup dispense with any trusted setup to eliminate security backdoor and enhance transparency. They are increasingly deployed in diverse decentralized applications on blockchains. One of the major concerns of practical deployment of range arguments on blockchains is the incurred gas cost and high computational overhead associated with blockchain miners. Hence, it is crucial to optimize the verification efficiency in range arguments to alleviate the deployment cost on blockchains and other decentralized platforms. In this paper, we present VeRange with several new zero-knowledge range arguments in the discrete logarithm setting, requiring only \(c \sqrt {N/\log N}\) group exponentiations for verification, where N is the number of bits to represent a range and c is a small constant, making them concretely efficient for blockchain deployment with a very low gas cost. Furthermore, VeRange is aggregable, allowing a prover to simultaneously prove T range arguments in a single argument, requiring only \(O(\sqrt {TN/\log (TN)}) + T\) group exponentiations for verification. We deployed VeRange on Ethereum, achieving the fastest verification runtime and the lowest gas cost among the discrete-logarithm-based range arguments in practice.

3. Mining Attack with Zero Knowledge in the Blockchain

Venue: ASIACCS | Year: 2025 | Citations: 0 Authors: Jiaping Yu, Shang Gao 0006, Rui Song, Zhiping Cai, Bin Xiao 0001 et al.

Mining attacks remain a serious threat to Proof-of-Work (PoW) blockchain systems, as malicious miners can deviate from standard mining rules to gain extra rewards. While classic selfish mining tactics conceal entire blocks or release them at once to cause forks, we extend the strategy space by introducing partial block sharing and leveraging zero-knowledge proofs. Specifically, we propose a novel Mining Attack with Zero Knowledge, encompassing two main strategies: Partial Selfish Mining (PSM) and its advanced variant Advanced PSM (A-PSM). By selectively releasing only partial block data, an attacker can attract rational miners to join its private branch without fully revealing the mined block. A zero-knowledge-proof-based mechanism ensures that these rational miners can be convinced of the block’s validity without learning its complete content, thereby incentivizing them to collude for higher individual gains. Our theoretical and experimental results show that, under certain conditions on mining power distribution and network latency, PSM can yield higher rewards than both honest and selfish mining, and A-PSM attackers can achieve profits that match or exceed selfish mining and even honest mining. This work highlights a novel zero-knowledge-enabled collusion threat in blockchain mining and calls for broader security measures to protect against such sophisticated strategies.

⚡ Latest Pre-Prints

1. Wood traceability system using blockchain and zero-knowledge proof

Published: 2022-11-21 Authors: Kyohei Shibano, Tohru Nakajima, Gento Mogi

The system proposed in this study uses zero-knowledge proof (ZKP) to verify the traceability of wood recorded in a public blockchain. Wood is a byproduct of several states, ranging from standing trees to logs, lumber, and wood products (hereinafter ``wood objects’’). The advantage of using the blockchain for record keeping is that participants can freely record the information at their discretion, without any restrictions. However, the openness of the blockchain may allow a malicious third party to introduce disinformation. In this study, we employ ZKP and near-field communication (NFC) chips to eliminate the possibility of disinformation introduction. ZKP is used to prove/validate changes in the state of wood objects, and the unique nonce associated with that state is encrypted and recorded on an NFC chip. The nonce is concealed and id of the wood object is defined as hash value of this nonce. We developed a prototype system based on an Android application and an Ethereum smart contract. We confirm that wood traceability and verification can be performed using the prototype system.

2. Location-aware Verification for Autonomous Truck Platooning Based on Blockchain and Zero-knowledge Proof

Published: 2023-05-26 Authors: Wanxin Li, Collin Meese, Zijia Zhong, Hao Guo, Mark Nejad

Platooning technologies enable trucks to drive cooperatively and automatically, which bring benefits including less fuel consumption, more road capacity and safety. In order to establish trust during dynamic platoon formation, ensure vehicular data integrity, and guard platoons against potential attackers, it is pivotal to verify any given vehicle’s identity information before granting it access to join a platoon. To address this concern in dynamic truck platooning, we present a novel location-aware and privacy-preserving verification protocol based on zero-knowledge proof and permissioned blockchain. By performing the verification process within the spatially-local area defined by a given platoon, our system can provide lower latency and communication overhead compared to a location-agnostic blockchain system. We prototype the proposed system and perform benchmark tests on the Hyperledger platform. The experimental results show that our system is suitable for real-world truck platooning.

3. Buck You: Designing Easy-to-Onboard Blockchain Applications with Zero-Knowledge Login and Sponsored Transactions on Sui

Published: 2024-04-05 Authors: Eason Chen, Zimo Xiao, Justa Liang, Damien Chen, Pierce Hung, Kostas Kryptos Chalkias

In this paper, we developed a blockchain application to demonstrate the functionality of Sui’s recent innovations: Zero Knowledge Login and Sponsored Transactions. Zero Knowledge Login allows users to create and access their blockchain wallets just with their OAuth accounts (e.g., Google, Facebook, Twitch), while Sponsored Transactions eliminate the need for users to prepare transaction fees, as they can delegate fees to sponsors’ accounts. Additionally, thanks to Sui’s Storage Rebate feature, sponsors in Sponsored Transactions can profit from the sponsorship, achieving a win-win and sustainable service model. Zero Knowledge Login and Sponsored Transactions are pivotal in overcoming key challenges novice blockchain users face, particularly in managing private keys and depositing initial transaction fees. By addressing these challenges in the user experience of blockchain, Sui makes the blockchain more accessible and engaging for novice users and paves the way for the broader adoption of blockchain applications in everyday life.

4. SurferMonkey: A Decentralized Anonymous Blockchain Intercommunication System via Zero Knowledge Proofs

Published: 2022-10-24 Authors: Miguel Díaz Montiel, Rachid Guerraoui, Pierre-Louis Roman

Blockchain intercommunication systems enable the exchanges of messages between blockchains. This interoperability promotes innovation, unlocks liquidity and access to assets. However, blockchains are isolated systems that originally were not designed for interoperability. This makes cross-chain communication, or bridges for short, insecure by nature. More precisely, cross-chain systems face security challenges in terms of selfish rational players such as maximal extractable value (MEV) and censorship. We propose to solve these challenges using zero knowledge proofs (ZKPs) for cross-chain communication. Securing cross-chain communication is remarkably more complex than securing single-chain events as such a system must preserve user security against both on- and off-chain analysis. To achieve this goal, we propose the following pair of contributions: the DACT protocol and the SurferMonkey infrastructure that supports the DACT protocol. The DACT protocol is a global solution for the anonymity and security challenges of agnostic blockchain intercommunication. DACT breaks on- and off-chain analysis thanks to the use of ZKPs. SurferMonkey is a decentralized infrastructure that implements DACT in practice. Since SurferMonkey works at the blockchain application layer, any decentralized application (dApp) can use SurferMonkey to send any type of message to a dApp on another blockchain. With SurferMonkey, users can neither be censored nor be exposed to MEV. By applying decentralized proactive security, we obtain resilience against selfish rational players, and raise the security bar against cyberattacks. We have implemented a proof of concept (PoC) of SurferMonkey by reverse engineering Tornado Cash and by applying IDEN3 ZKP circuits. SurferMonkey enables new usecases, ranging from anonymous voting and gaming, to a new phase of anonymous decentralized finance (aDeFi).

5. SoK: Bridging Trust into the Blockchain. A Systematic Review on On-Chain Identity

Published: 2024-07-24 Authors: Awid Vaziry, Kaustabh Barman, Patrick Herbke

The ongoing regulation of blockchain-based services and applications requires the identification of users who are issuing transactions on the blockchain. This systematic review explores the current status, identifies research gaps, and outlines future research directions for establishing trusted and privacy-compliant identities on the blockchain (on-chain identity). A systematic search term was applied across various scientific databases, collecting 2232 potentially relevant research papers. These papers were narrowed down in two methodologically executed steps to 98 and finally to 13 relevant sources. The relevant articles were then systematically analyzed based on a set of screening questions. The results of the selected studies have provided insightful findings on the mechanisms of on-chain identities. On-chain identities are established using zero-knowledge proofs, public key infrastructure/certificates, and web of trust approaches. The technologies and architectures used by the authors are also highlighted. Trust has emerged as a key research gap, manifesting in two ways: firstly, a gap in how to trust the digital identity representation of a physical human; secondly, a gap in how to trust identity providers that issue identity confirmations on-chain. Potential future research avenues are suggested to help fill the current gaps in establishing trust and on-chain identities.

6. Enhanced Security and Efficiency in Blockchain with Aggregated Zero-Knowledge Proof Mechanisms

Published: 2024-02-06 Authors: Oleksandr Kuznetsov, Alex Rusnak, Anton Yezhov, Dzianis Kanonik, Kateryna Kuznetsova, Stanislav Karashchuk

Blockchain technology has emerged as a revolutionary tool in ensuring data integrity and security in digital transactions. However, the current approaches to data verification in blockchain systems, particularly in Ethereum, face challenges in terms of efficiency and computational overhead. The traditional use of Merkle Trees and cryptographic hash functions, while effective, leads to significant resource consumption, especially for large datasets. This highlights a gap in existing research: the need for more efficient methods of data verification in blockchain networks. Our study addresses this gap by proposing an innovative aggregation scheme for Zero-Knowledge Proofs within the structure of Merkle Trees. We develop a system that significantly reduces the size of the proof and the computational resources needed for its generation and verification. Our approach represents a paradigm shift in blockchain data verification, balancing security with efficiency. We conducted extensive experimental evaluations using real Ethereum block data to validate the effectiveness of our proposed scheme. The results demonstrate a drastic reduction in proof size and computational requirements compared to traditional methods, making the verification process more efficient and economically viable. Our contribution fills a critical research void, offering a scalable and secure solution for blockchain data verification. The implications of our work are far-reaching, enhancing the overall performance and adaptability of blockchain technology in various applications, from financial transactions to supply chain management.

7. Zero-Knowledge Proof-Based Consensus for Blockchain-Secured Federated Learning

Published: 2025-03-17 Authors: Tianxing Fu, Jia Hu, Geyong Min, Zi Wang

Federated learning (FL) enables multiple participants to collaboratively train machine learning models while ensuring their data remains private and secure. Blockchain technology further enhances FL by providing stronger security, a transparent audit trail, and protection against data tampering and model manipulation. Most blockchain-secured FL systems rely on conventional consensus mechanisms: Proof-of-Work (PoW) is computationally expensive, while Proof-of-Stake (PoS) improves energy efficiency but risks centralization as it inherently favors participants with larger stakes. Recently, learning-based consensus has emerged as an alternative by replacing cryptographic tasks with model training to save energy. However, this approach introduces potential privacy vulnerabilities, as the training process may inadvertently expose sensitive information through gradient sharing and model updates. To address these challenges, we propose a novel Zero-Knowledge Proof of Training (ZKPoT) consensus mechanism. This method leverages the zero-knowledge succinct non-interactive argument of knowledge proof (zk-SNARK) protocol to validate participants’ contributions based on their model performance, effectively eliminating the inefficiencies of traditional consensus methods and mitigating the privacy risks posed by learning-based consensus. We analyze our system’s security, demonstrating its capacity to prevent the disclosure of sensitive information about local models or training data to untrusted parties during the entire FL process. Extensive experiments demonstrate that our system is robust against privacy and Byzantine attacks while maintaining accuracy and utility without trade-offs, scalable across various blockchain settings, and efficient in both computation and communication.

8. Zero-knowledge Based Proof-chain – A methodology for blockchain-partial system

Published: 2021-06-29 Authors: Yuqi Bai, Lei Luo

Intuitively there is a drastic distinction between the pure decentralized block-chain systems like Defis and those that only utilize block-chain as an enhancing technology but remain centralized with real-world business model and conventional technologies like database, application server, etc. Our study explores extensively this distinction from a methodological point of view, classifies them into blockchain-complete and blockchain-partial, analyzes key features of the two types, and reveals the root cause of this distinction. We analyze the function or, in more strong words, the “ultimate purpose” of blockchain in the blockchain-partial systems, and present a conceptual model we named proof-chain that quite satisfactorily represented the general paradigm of blockchain in blockchain-partial systems. A universal tension between strength of proof-chain and privacy is then revealed and the zero-knowledge based proof-chain takes shape. Several case studies demonstrate the explaining power of our proof-chain methodology. We then apply proof-chain methodology to the analysis of the ecosystem of a collaborating group of blockchain-partial systems, representing the paradigm of public and private data domain whose border the proof-chain crosses. Finally, some derived guidelines from this methodology speak usefulness of our methodology.

9. Fairness, Integrity, and Privacy in a Scalable Blockchain-based Federated Learning System

Published: 2021-11-11 Authors: Timon Rückel, Johannes Sedlmeir, Peter Hofmann

Federated machine learning (FL) allows to collectively train models on sensitive data as only the clients’ models and not their training data need to be shared. However, despite the attention that research on FL has drawn, the concept still lacks broad adoption in practice. One of the key reasons is the great challenge to implement FL systems that simultaneously achieve fairness, integrity, and privacy preservation for all participating clients. To contribute to solving this issue, our paper suggests a FL system that incorporates blockchain technology, local differential privacy, and zero-knowledge proofs. Our implementation of a proof-of-concept with multiple linear regression illustrates that these state-of-the-art technologies can be combined to a FL system that aligns economic incentives, trust, and confidentiality requirements in a scalable and transparent system.

10. Scalable Zero-Knowledge Proofs for Verifying Cryptographic Hashing in Blockchain Applications

Published: 2024-07-03 Authors: Oleksandr Kuznetsov, Anton Yezhov, Vladyslav Yusiuk, Kateryna Kuznetsova

Zero-knowledge proofs (ZKPs) have emerged as a promising solution to address the scalability challenges in modern blockchain systems. This study proposes a methodology for generating and verifying ZKPs to ensure the computational integrity of cryptographic hashing, specifically focusing on the SHA-256 algorithm. By leveraging the Plonky2 framework, which implements the PLONK protocol with FRI commitment scheme, we demonstrate the efficiency and scalability of our approach for both random data and real data blocks from the NEAR blockchain. The experimental results show consistent performance across different data sizes and types, with the time required for proof generation and verification remaining within acceptable limits. The generated circuits and proofs maintain manageable sizes, even for real-world data blocks with a large number of transactions. The proposed methodology contributes to the development of secure and trustworthy blockchain systems, where the integrity of computations can be verified without revealing the underlying data. Further research is needed to assess the applicability of the approach to other cryptographic primitives and to evaluate its performance in more complex real-world scenarios.

🧠 Architectural & Methodological Insights

• Zero‑knowledge as a universal privacy layer – Across the surveyed works, ZKPs are no longer a niche gadget for confidential transactions; they appear as the core primitive for data integrity (DART), range verification (VeRange), cross‑chain anonymity (SurferMonkey), and consensus (ZKPoT). This signals a shift toward treating ZKPs as a foundational protocol stack that can be composed with storage, consensus, and identity modules.

• Integration with decentralized storage and erasure coding – DART demonstrates a tight coupling of ZK‑based auditing with erasure‑coded storage and accumulator‑based batch verification, indicating a trend of embedding ZKPs directly into the data‑layer of blockchain‑backed storage networks.

• Transparent and aggregatable constructions – VeRange’s transparent‑setup range arguments and its aggregation across multiple proofs illustrate a move toward eliminating trusted setups while scaling verification cost linearly with the number of statements. Similar aggregation ideas appear in the “Aggregated Zero‑Knowledge Proof Mechanisms” pre‑print, pointing to a broader architectural pattern of proof compression for on‑chain verification.

• Zero‑knowledge‑enabled consensus and incentive mechanisms – The Mining Attack with Zero Knowledge paper and the ZKPoT consensus design show that ZKPs are being used to reshape incentive structures, either by enabling novel attack vectors or by replacing PoW/PoS with succinct proof‑of‑training. This reflects an emerging research direction where consensus itself is expressed as a ZK‑verifiable statement.

• Hybrid on‑chain/off‑chain privacy architectures – Works such as the wood traceability system, location‑aware truck platooning, and the on‑chain identity SoK combine ZKPs with external hardware (NFC chips) or permissioned ledgers to achieve low‑latency, privacy‑preserving verification, suggesting a pattern of hybrid architectures that offload heavy computation while preserving on‑chain auditability.

Overall, the subfield is converging on modular, aggregatable, and transparent ZK‑centric stacks that can be layered on top of storage, consensus, and identity subsystems, with an emphasis on practical deployment (Ethereum, Hyperledger, Sui) and on reducing on‑chain gas and communication costs.

🚀 Critical Research Gaps

1. Scalable verification for massive batch operations – While DART introduces batch verification for data retrieval, and VeRange offers aggregation for range proofs, there is no unified framework that simultaneously handles heterogeneous proof types (range, storage, identity) in a single batch. The lack of cross‑proof aggregation limits throughput for complex applications that need multiple ZK statements per transaction.

2. Robustness of ZK‑based consensus against adaptive adversaries – The “Mining Attack with Zero Knowledge” paper reveals that partial block disclosure combined with ZKPs can create new collusion channels. Existing ZK‑based consensus designs (e.g., ZKPoT) do not formally model adaptive adversaries who can request selective proof openings or manipulate network latency. A formal security model and mitigation strategies are missing.

3. Transparent setup without trusted hardware for universal circuits – VeRange achieves a transparent setup for discrete‑logarithm range arguments, yet many other primitives (e.g., zk‑SNARKs used in ZKPoT, aggregated proofs in the 2024 aggregation pre‑print) still rely on a trusted setup or specialized hardware. A gap remains in constructing universally trusted‑setup‑free circuits for arbitrary statements relevant to blockchain workloads.

4. Interoperability of ZK‑enhanced identity across heterogeneous ledgers – The SoK on on‑chain identity enumerates ZKP‑based identity schemes but does not provide a cross‑chain protocol that preserves privacy while enabling credential verification on both permissioned and permissionless networks. This hampers the deployment of unified identity solutions in multi‑chain ecosystems.

💡 High‑Impact Open Problems

1. Unified Cross‑Proof Aggregation Protocol
   Design a protocol that can aggregate heterogeneous ZK proofs (range, storage audit, identity attestation) into a single succinct proof verifiable on‑chain with sub‑linear verification cost. The solution should support dynamic addition of proof types and maintain zero‑knowledge guarantees for each component.

2. Adaptive‑Adversary‑Resilient ZK Consensus Model
   Develop a formal security model for ZK‑based consensus that captures adaptive adversaries capable of selective proof disclosure and network manipulation. Propose concrete protocol extensions (e.g., randomized proof blinding, time‑locked commitments) and prove that they preserve liveness, safety, and privacy under the model.

3. Transparent‑Setup Universal zk‑SNARK Compiler for Blockchain Primitives
   Build a compiler that transforms arbitrary arithmetic circuits representing common blockchain operations (e.g., Merkle‑tree verification, state transition, cross‑chain message passing) into transparent‑setup zk‑SNARKs with comparable proof size and verification time to trusted‑setup counterparts. Evaluate the compiler on real‑world workloads such as the “Scalable Zero‑Knowledge Proofs for Verifying Cryptographic Hashing” and the “Enhanced Security and Efficiency in Blockchain with Aggregated Zero‑Knowledge Proof Mechanisms” implementations.

Tackling any of these problems would directly address the identified gaps, push the architectural maturity of ZK‑enabled blockchains forward, and open new avenues for scalable, privacy‑preserving decentralized applications.