Blockchain Papers

Murali Krishna Pasupuleti

Abstract: Algebraic geometry offers a powerful and elegant mathematical framework for the design and analysis of modern cryptographic protocols. This research paper investigates the application of algebraic geometry methods—such as elliptic curves, abelian varieties, and projective algebraic structures—in enhancing the security, efficiency, and scalability of cryptographic systems. By bridging advanced algebraic structures with cryptographic primitives, the study demonstrates how algebraic geometry enables the construction of secure public key protocols, zero-knowledge proofs, and post-quantum resilient schemes. Through theoretical modeling, performance benchmarking, and comparative analysis with classical cryptographic approaches, the paper illustrates the advantages of algebraic geometry in terms of computational hardness assumptions, structural integrity, and potential for innovation in secure communications. The findings contribute to the evolving landscape of cryptography by positioning algebraic geometry as a foundational tool in next-generation cryptographic protocol design. Keywords: algebraic geometry, cryptographic protocols, elliptic curves, public key cryptography, post-quantum cryptography, projective varieties, zero-knowledge proofs, secure communication, mathematical cryptography, abelian varieties

Kun Liu

In the context of global cross-border payments exceeding $150 trillion, traditional mediation architectures, such as SWIFT, face challenges due to high costs, inefficiencies, and fraud risks. However, blockchain technology become an important driver of innovation in cross-border payments with the characteristics of decentralization, real-time and immutable. This paper aims to answer two core questions: Blockchain technology how to improve the efficiency of cross-border payments through smart contracts, cross-chain protocols and other technical features? How to identify and prevent key risks such as private key security and regulatory conflicts? Through the logical framework of "technical basis - efficiency analysis - risk identification - prevention and control strategy", combined with case comparison (such as RippleNet and SWIFT) and quantitative data (such as Stellar network $0.01 / transaction cost). This paper systematically analyzes the role of blockchain in disintermediation, cost compression, and transparency optimization. Besides, the risks of technological vulnerabilities, regulatory fragmentation and market volatility are revealed. Then, this paper proposes a collaborative governance scheme of hybrid architecture, zero-knowledge proof and multilateral regulatory sandbox. Research finding, blockchain technology can reduce cross-border payment time to seconds and reduce costs by more than 90%, but it needs to deal with challenges such as throughput constraints, conflicting regulatory standards and the volatility of digital currencies. It is suggested that future research focus technology optimization, multilateral regulatory collaboration and market ecological integration, provide theoretical and practical support for building an efficient and secure global payment system.

Shunqing Wu, Lifei Wei, Sean M. Wu, Lei Zhang

While blockchain’s immutability ensures data integrity, it also poses significant challenges when dealing with illegal or erroneous data that require modification. The concept of redactable blockchain has emerged, utilizing Chameleon Hash (CH) and subsequent Policy-based Chameleon Hash (PCH) for controlled data editing. However, current redactable blockchain implementations exhibit significant limitations, particularly in their inability to separate data editing from policy modification and their insufficient support for decentralized management of diverse editing operations. To address these issues, this paper initially introduces the concept of Flexible Policy Chameleon Hash (FPCH), which integrates PCH with non-interactive zero-knowledge proofs to enable enhanced policy management flexibility. Moreover, this paper proposes a Redactable Blockchain Framework with Fine-grained Access Control (RBFAC) based on FPCH. The RBFAC framework employs a hybrid cryptographic approach to separate the right of data editing from policy modification. The framework also provides essential functionalities, including editing accountability, key tracking and revocation mechanisms, and policy privacy protection. Finally, experimental evaluations demonstrate that the RBFAC framework maintains acceptable performance overhead while delivering these advanced features. The results indicate that the proposed solution addresses the limitations of existing redactable blockchain systems, offering a more flexible and secure approach to controlled data editing in blockchain environments.

C. Aparna, S. Radha, C. Aarthi, K. M. Karthick Raghunath

ABSTRACT Mobile Ad hoc networks (MANETs) are key for applications in which flexibility and organization are paramount, but the security of such networks entails threats that can exploit the vulnerability of their open architecture, resulting in various attacks. To address such issues, a novel architectural framework is always required. One such framework is introduced, namely, the HoneyFed Secure Architecture (HFSA), which provides the combination of an advanced honey encryption system with federated learning‐based decentralized security to improve the security of MANET. Honey encryption, on the other hand, employs adaptive deception techniques to generate plausible decoy data on decryption failure, employs dynamic key management for tamper resistance, and provides perfect authentication through multi‐factor methods and zero‐knowledge proofs. We found that federated learning offers decentralized model training, where nodes jointly train local models while exchanging progress updates without exposing raw data, enabling 81.4% more detections of emerging threats while preserving data privacy. Using the proposed HFSA approach achieves a 78% protection improvement against attacks and a 71% reduction in unauthorized access. HFSA offers a robust and scalable framework of security that uses continuous learning and adaptation to the vulnerabilities of the MANETs to enhance network resilience.

William J Buchanan

Some of our current public key methods use a trap door to implement digital signature methods. This includes the RSA method, which uses Fermat's little theorem to support the creation and verification of a digital signature. The problem with a back-door is that the actual trap-door method could, in the end, be discovered. With the rise of PQC (Post Quantum Cryptography), we will see a range of methods that will not use trap doors and provide stronger proof of security. In this case, we use hash-based signatures (as used with SPHINCS+) and Fiat Shamir signatures using Zero Knowledge Proofs (as used with Dilithium).

Manuel J. C. S. Reis

The rapid expansion of 5G networks and edge computing has amplified security challenges in Internet of Things (IoT) environments, including unauthorized access, data tampering, and DDoS attacks. This paper introduces EdgeChainGuard, a hybrid blockchain-based authentication framework designed to secure 5G-enabled IoT systems through decentralized identity management, smart contract-based access control, and AI-driven anomaly detection. By combining permissioned and permissionless blockchain layers with Layer-2 scaling solutions and adaptive consensus mechanisms, the framework enhances both security and scalability while maintaining computational efficiency. Using synthetic datasets that simulate real-world adversarial behaviour, our evaluation shows an average authentication latency of 172.50 s and a 50% reduction in gas fees compared to traditional Ethereum-based implementations. The results demonstrate that EdgeChainGuard effectively enforces tamper-resistant authentication, reduces unauthorized access, and adapts to dynamic network conditions. Future research will focus on integrating zero-knowledge proofs (ZKPs) for privacy preservation, federated learning for decentralized AI retraining, and lightweight anomaly detection models to enable secure, low-latency authentication in resource-constrained IoT deployments.

Seun Adeoye

The fast digital transformation of healthcare systems has brought electronic health records (EHRs) into wide usage to enhance patient care and provide better data access. The need for better security grows more pungent as cybersecurity and quantum computing threats against traditional cryptographic approaches become more prevalent. This paper develops a Blockchain-Enabled Post-Quantum Cryptographic framework for protecting EHRs. The combination of blockchain technology with PQC safeguards healthcare data through decentralised distribution, unalterable data storage, and complete system transparency, and PQC prevents anticipated quantum computing vulnerabilities. Security and privacy improve in the proposed framework by combining lattice-based cryptography, hash-based signatures, and zero-knowledge proofs. Smart contracts enable the framework to enforce access policies and maintain regulatory compliance through its functionality. A performance analysis of this framework shows it can effectively secure EHRs through efficient and scalable implementation. The research demonstrates that PQC and blockchain offer healthcare organisations a secure protection solution for EHRs that fights evolving cyber threats within trustworthy healthcare systems.

A. Althaf Ali, M. A. Gunavathie, V. Srinivasan, M. Aruna · 6 authors

The integration of smart city applications with healthcare has revolutionized patient monitoring and medical data management. However, ensuring the privacy and security of Electronic Health Records (EHR) remains a critical challenge, especially in IoT-based environments with resource-constrained devices. This paper proposes a novel Blockchain-Enabled Federated Learning (BFL) framework to enhance privacy preservation in EHR processing. The proposed framework leverages zero-knowledge proofs (ZKP) for authentication and homomorphic encryption for secure computation, ensuring robust data security without exposing raw patient data. Federated Learning (FL) enables decentralized model training across IoT devices, reducing privacy risks while maintaining data utility. Additionally, blockchain technology enhances the integrity and transparency of EHR transactions by creating a tamper-proof ledger. The performance of the proposed BFL framework is evaluated based on data utility, model accuracy, execution time, and scalability across varying sizes of EHR datasets. Results demonstrate improved privacy preservation, reduced computational overhead, and enhanced model efficiency, making it a promising approach for secure and privacy-aware IoT-based smart healthcare systems.

Butrus Mbimbi, David Murray, Michael Wilson

This research presents a novel framework and experimental results that combine zero-knowledge proofs (ZKPs) with private blockchain technology to safeguard whistleblower privacy while ensuring secure digital evidence submission and verification. For example, whistleblowers involved in corporate fraud cases can submit sensitive financial records anonymously while maintaining the credibility of the evidence. The proposed framework introduces several key innovations, including a private blockchain implementation utilising proof-of-work (PoW) consensus to ensure immutable storage and thorough scrutiny of submitted evidence, with mining difficulty dynamically aligned to the sensitivity of the data. It also features an adaptive difficulty mechanism that automatically adjusts computational requirements based on the sensitivity of the evidence, providing tailored protection levels. In addition, a unique two-phase validation process is incorporated, which generates a digital signature from the evidence alongside random challenges, significantly improving security and authenticity. The integration of ZKPs enables iterative hash-based verification between parties (Prover and Verifier) while maintaining the complete privacy of the source data. This research investigates the whistleblower’s niche in traditional digital evidence management systems (DEMSs), prioritising privacy without compromising evidence integrity. Experimental results demonstrate the framework’s effectiveness in preserving anonymity while assuring the authenticity of the evidence, making it useful for judicial systems and organisations handling sensitive disclosures. This paper signifies notable progress in secure whistleblowing systems, offering a way to juggle transparency with informant confidentiality.

Yancheng Zhang, Mengxin Zheng, Xun Chen, Jingtong Hu · 8 authors

In the context of cloud computing, services are held on cloud servers, where the clients send their data to the server and obtain the results returned by server. However, the computation, data and results are prone to tampering due to the vulnerabilities on the server side. Thus, verifying the integrity of computation is important in the client-server setting. The cryptographic method known as Zero-Knowledge Proof (ZKP) is renowned for facilitating private and verifiable computing. ZKP allows the client to validate that the results from the server are computed correctly without violating the privacy of the server’s intellectual property. Zero-Knowledge Succinct NonInteractive Argument of Knowledge (zkSNARKs), in particular, has been widely applied in various applications like blockchain and verifiable machine learning. Despite their popularity, existing zkSNARKs approaches remain highly computationally intensive. For instance, even basic operations like matrix multiplication require an extensive number of constraints, resulting in significant overhead. In addressing this challenge, we introduce $z k V C$, which optimizes the ZKP computation for matrix multiplication, enabling rapid proof generation on the server side and efficient verification on the client side. zkVC integrates optimized ZKP modules, such as Constraint-reduced Polynomial Circuit (CRPC) and Prefix-Sum Query (PSQ), collectively yielding a more than $\mathbf{1 2}$-fold increase in proof speed over prior methods. The code is available at https://github.com/UCF-Lou-Lab-PET/zkformer.

Janaka Ishan Senarathna

Blockchain technology has transformed secure data management by employing a decentralized framework that fundamentally depends on cryptographic methods. This paper investigates how hash functions (e.g., SHA-256), digital signatures (e.g., ECDSA), and Merkle trees enable blockchain’s core attributes—immutability, security, and transparency. A Python-based proof-of-concept demonstrates hashing’s pivotal role in linking blocks, ensuring resistance to tampering. The study assesses cryptography’s contributions, such as enhanced security, alongside limitations like quantum vulnerabilities and scalability constraints. It proposes future directions, including post-quantum cryptography and zero-knowledge proofs, to mitigate these challenges. Real-world applications in finance and supply chains highlight practical relevance. Findings confirm cryptography as the bedrock of blockchain, offering insights to bolster its resilience amid evolving technological demands.

Artem Chystiakov, Oleh Komendant, Kyrylo Riabov

This paper introduces the Cartesian Merkle Tree, a deterministic data structure that combines the properties of a Binary Search Tree, a Heap, and a Merkle tree. The Cartesian Merkle Tree supports insertions, updates, and removals of elements in $O(\log n)$ time, requires $n$ space, and enables membership and non-membership proofs via Merkle-based authentication paths. This structure is particularly suitable for zero-knowledge applications, blockchain systems, and other protocols that require efficient and verifiable data structures.

Adam Bennett, Jennifer Clarke

The rapid advancement of digital services and online interactions has highlighted the need for secure, user-centric identity management systems. Traditional identity solutions, often centralized and dependent on trusted third parties, pose challenges related to privacy, security, and control over personal data. Distributed Ledger Technology (DLT), particularly blockchain, offers a promising solution for decentralized identity management by enabling self-sovereign identities (SSI). Through the use of decentralized identifiers (DIDs) and verifiable credentials (VCs), DLT allows individuals to maintain full control over their personal information, eliminating the need for intermediaries while ensuring data integrity and privacy. This paper explores the key principles of DLT-based decentralized identity management, discussing its potential to enhance privacy, security, and interoperability in digital ecosystems. We examine the various technical frameworks, challenges, and standards in the field, with a focus on the integration of DLT with emerging technologies such as zero-knowledge proofs (ZKPs) and secure multiparty computation (SMPC). Additionally, we evaluate real-world use cases, from financial services to healthcare, and the role of regulatory frameworks in shaping the future of decentralized identity systems. Ultimately, DLT presents a paradigm shift in identity management, offering scalable, transparent, and trusted solutions for the digital age.

Sudheer Obbu

Zero Trust Architecture (ZTA) offers a critical security framework for AI-powered cloud systems, replacing traditional perimeter-based defenses with the principle of "never trust, always verify." As organizations deploy increasingly sophisticated AI workloads in distributed cloud environments, they face unique and acute security challenges including model poisoning, adversarial attacks, and extraction attempts targeting valuable intellectual property. ZTA addresses these challenges through continuous authentication, least privilege access, micro-segmentation, and ongoing monitoring specifically calibrated for AI systems. Implementation requires balancing security with performance considerations, managing complexity, addressing skill gaps, and overcoming technical debt in legacy systems. Emerging approaches including AI-powered security tools, zero-knowledge proofs, hardware-based security measures, and standardized frameworks for autonomous systems are shaping the future of AI security in cloud environments, enabling organizations to realize the benefits of AI innovation while maintaining robust protection.

Harsh Kumar Verma

With the rapid growth of the Internet of Things (IoT), maintaining data integrity, confidentiality, and authentication is now an imperative challenge. Most conventional cryptographic solutions cannot satisfy the specific constraints of IoT environments, which include limited computational resources, energy efficiency, and scalability. This study proposes a lightweight hybrid cryptographic framework combining Authenticated Encryption with Associated Data (AEAD) and Verifiable Random Functions (VRF) with Elliptic Curve Digital Signature Algorithm (ECDSA). The hybrid framework is intended to offer robust data integrity, secure authentication, and efficient encryption mechanisms with minimal computational overhead. Our solution makes use of AEAD (AES-GCM or ChaCha20-Poly1305) in order to establish both confidentiality and integrity within a single encryption process and with much less processing time than in traditional approaches such as AES-CTR with HMAC. Use of VRF guarantees that cryptographic algorithms result in verifiable randomness that increases replay attack and unauthorized entry security. ECDSA is utilized for lightweight digital signatures, providing non-repudiation without the computational overhead being higher than RSA-based integrity mechanisms. To ensure the efficacy of our methodology, we performed thorough benchmarking tests comparing AEAD + VRF + ECDSA with conventional cryptographic methods like AES-CTR + HMAC and integrity verification based on RSA. It is revealed by our benchmarks that our hybrid solution considerably cuts down encryption time, minimizes CPU utilization, and maximizes memory usage, thus being very suitable for resource-poor IoT devices. In contrast to AES-CTR + HMAC, which needs independent encryption and authentication phases, AEAD's hybrid approach has the least storage footprint and computational overhead. Furthermore, avoiding a dedicated verification step (necessary in HMAC-based designs) adds to system responsiveness. Our work adds to the literature through a scalable, effective, and secure cryptographic framework optimized for IoT use cases such as secure messaging, sensor data encryption, and access control in distributed systems. Real-world deployment in IoT platforms, post-quantum cryptographic augmentation, and implementing zero-knowledge proofs (ZKPs) for improved privacy-preserving authentication are next steps. By solving major problems in IoT security, our hybrid approach provides an efficient yet reliable alternative to state-of-the-art cryptographic solutions to guarantee end-to-end data confidentiality and integrity within contemporary IoT infrastructures.

Jayesh Solanki

Integrity and transparency in electoral procedures are essential for the actual functioning of democratic countries. The present voting systems often face numerous issues such as vote rigging, counterfeit ballots, lack of transparency, and inefficiencies. Blockchain-enabled voting systems are promising, but they face challenges in maintaining public trust due to technical concerns, such as transparency, security, privacy, and scalability. The architecture of a Hyperledger-based framework is proposed to design and construct a robust and secure prototype for a blockchain-enabled voting system. Effective algorithms for key electoral processes such as identity management for voter authentication, vote casting, vote counting and vote tallying, using multi-signature validation are deployed. Contemporary cryptographic techniques, such as zero-knowledge proofs, homographic encryption, and digital signatures, ensure that votes are encrypted and anonymized, protecting voter privacy and facilitating a verifiable election process. Through an exploratory work, the recommended prototype using Hyperledger Fabric is compared with conventional electoral systems based on key parameters. This study demonstrates that a blockchain-based election system is able to maintain the integrity and efficiency of state-of-the-art technology by recommending a robust and secure prototype for conducting transparent and verifiable elections.

Julia Butte, André Platzer

Abstract This paper introduces semi-competitive differential game logic $$\textsf {dG}\mathcal {L}_{sc}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>dG</mml:mi> <mml:msub> <mml:mi>L</mml:mi> <mml:mrow> <mml:mi>sc</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , which enables verification of safety-critical applications that involve interactions between two agents. In $$\textsf {dG}\mathcal {L}_{sc}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>dG</mml:mi> <mml:msub> <mml:mi>L</mml:mi> <mml:mrow> <mml:mi>sc</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , these interactions are specified as games on hybrid systems with two players that may collaborate with each other when helpful and may compete when necessary. The players in the hybrid games of $$\textsf {dG}\mathcal {L}_{sc}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>dG</mml:mi> <mml:msub> <mml:mi>L</mml:mi> <mml:mrow> <mml:mi>sc</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> have individual goals that may overlap, leading to nonzero-sum games. This makes $$\textsf {dG}\mathcal {L}_{sc}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>dG</mml:mi> <mml:msub> <mml:mi>L</mml:mi> <mml:mrow> <mml:mi>sc</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> especially well-suited for verifying situations where players, e.g., share safety objectives but otherwise pursue different goals, so that zero-sum assumptions lead to overly conservative results. Additionally, $$\textsf {dG}\mathcal {L}_{sc}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>dG</mml:mi> <mml:msub> <mml:mi>L</mml:mi> <mml:mrow> <mml:mi>sc</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> solves the subtlety that even though each player may benefit from knowledge of the other player’s goals, e.g., concerning shared safety objectives, unsafe situations might still occur if every player were to mutually assume the other player would act to avoid unsafety. The syntax and semantics, as well as a sound and relatively complete proof calculus are presented for $$\textsf {dG}\mathcal {L}_{sc}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>dG</mml:mi> <mml:msub> <mml:mi>L</mml:mi> <mml:mrow> <mml:mi>sc</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> . The relationship between $$\textsf {dG}\mathcal {L}_{sc}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>dG</mml:mi> <mml:msub> <mml:mi>L</mml:mi> <mml:mrow> <mml:mi>sc</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> and zero-sum differential game logic $$\textsf {dG}\mathcal {L}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>dG</mml:mi> <mml:mi>L</mml:mi> </mml:mrow> </mml:math> is discussed and the purpose of $$\textsf {dG}\mathcal {L}_{sc}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>dG</mml:mi> <mml:msub> <mml:mi>L</mml:mi> <mml:mrow> <mml:mi>sc</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> illustrated in a canonical example.

Pritesh Panda, Dhruv Bharara, Sarthak Singh, Bhargav Singh

Decentralized finance (DeFi) lending platforms often require over-collateralization, excluding users without substantial crypto holdings. This paper introduces LFG, a novel DeFi protocol that leverages on-chain social profiles and tokenized reputation to assess creditworthiness. By integrating Ethereum smart contracts with Layer-2 solutions (Ethereum, Polygon), decentralized storage (IPFS) and zero-knowledge proofs, LFG enables undercollateralized loans while preserving privacy. We present a technical architecture, analyze security risks, and compare LFGs with traditional models using quantitative metrics. The results show a 40% reduction in collateral requirements for users with high reputation scores on the chain.

Damiano Di Francesco Maesa, Matteo Loporchio, Frank Tietze

This paper considers the application scenario of Intellectual Property (IP) management, a business process yet to fully embrace digitisation and the advantages it brings. We propose to leverage Distributed Ledger Technology (DLT) to digitise license agreements management by providing automated and trustworthy royalty computation, transaction execution, and payment distribution. This can be achieved by employing smart licenses, i.e., bundles of smart contracts implementing the royalty logic of license agreements. To provide scalability, flexibility, and resilience, we propose to deploy smart licenses on a network of networks model, i.e., a set of heterogeneous networks potentially running different DLT protocols and connected by cross-chain information exchange protocols. A novel advantage of the network of networks approach is that it allows for the use of private values for royalty computation, which is impossible in the traditional model. Of course, supporting private DLT networks requires privacy-preserving cross-chain schemes, a still open problem in the literature. This is why we present two alternative privacy-preserving cross-chain schemes for our considered application scenario of license agreements management, one based on Homomorphic Encryption (HE) and the other on Zero-Knowledge (ZK) proofs. Besides discussing their theoretical advantages and drawbacks, we present an experimental evaluation of a prototype implementation of smart licenses based on both schemes. • We propose a network of networks model that enhances scalability in smart license ecosystems. • The proposed model allows smart licenses to leverage data from heterogeneous networks, including private ones. • We compare two methods for privacy-preserving cross-chain communication: homomorphic encryption and zero-knowledge proofs. • We experimentally evaluate and compare two different privacy-preserving smart license implementations.

Pulkit Sharma

The rapid advancement of quantum computing presents a fundamental challenge to modern cryptographic security, particularly in the domain of hash functions that ensure data integrity, authentication, and blockchain security. Traditional crypto graphic hash functions such as SHA-256, SHA-3, and BLAKE2 rely on computational hardness assumptions that become obsolete in the presence of large-scale quantum computers. Shor’s algorithm can efficiently break RSA and ECC-based cryptosys tems, while Grover’s algorithm reduces the security of traditional hash functions by square root complexity, significantly weakening their preimage and collision resistance. This quantum threat necessitates the development of post-quantum secure hashing techniques that remain resilient against both classical and quantum adversaries. This paper proposes Quantum Hashing, a novel cryptographic framework that integrates quantum entanglement, lattice-based cryptography, and hybrid quantum classical hashing to construct post-quantum secure hash functions. We introduce a formal model for Quantum Collision Resistance (QCR) and provide entropy-based ran domness enhancement to ensure unpredictable hash outputs. Unlike classical hashing approaches, our framework leverages the hardness of lattice problems (e.g., Shortest Vector Problem, Learning with Errors) to withstand quantum attacks while incorpo rating Quantum Key Distribution (QKD) mechanisms to enhance entropy and key management. Furthermore, we evaluate the security of Quantum Hashing under various attack models, comparing its resistance against Grover’s search and collision attacks. We benchmark its performance against NIST Post-Quantum Cryptography (PQC) final ists, including CRYSTALS-DILITHIUM, SPHINCS+, and Falcon, demonstrating that our approach offers superior resilience while maintaining computational feasibility. Additionally, we present an implementation of Quantum Hashing using Qiskit, show casing its practical applicability in quantum circuits and quantum-secure blockchain architectures. Our findings highlight that Quantum Hashing provides a scalable, entropy-efficient, and post-quantum resilient cryptographic primitive suitable for next-generation cryptographic applications. This work paves the way for secure post-quantum digital signatures, blockchain consensus mechanisms, and zero-knowledge proof systems that require tamper-resistant hashing in a quantum computing era.

Tiantian Zhang, Ying Wang, Bo Gong, Jianbo Xu · 6 authors

ABSTRACT Self‐sovereign identity management systems operate in open network environments and face security threats from semi‐trusted or malicious adversary models. In such environments, verifiable credentials are susceptible to attacks such as theft and forgery. In response to the privacy risks associated with verifiable credentials during issuance and revocation, this article proposes a privacy protection scheme for user information during the issuance and revocation processes of verifiable credentials in self‐sovereign identity management based on blockchain technology. First, a privacy‐preserving method that does not rely on a single identity provider and resists Sybil attacks has been designed using secure multi‐party computation cryptographic techniques. Second, the consortium blockchain committee nodes act as the issuer of verifiable credentials. By combining attribute commitments and zero‐knowledge proof techniques, the user's identity information is hidden, achieving the privacy protection goal during the issuance of verifiable credentials. Furthermore, in order to protect user privacy during the revocation of verifiable credentials (VCs), we employ a cryptographic accumulator technique to implement the revocation operation. This approach ensures the security of user privacy while effectively managing the revocation of credentials. Finally, this paper conducts a security analysis and performance evaluation of the proposed scheme. The results show that our scheme strikes a balance between security needs and time efficiency.

Alhad Daftardar, Jianqiao Mo, Joey Ah-kiow, Benedikt Bünz · 7 authors

Zero-Knowledge Proofs (ZKPs) are a rapidly growing technique for privacy-preserving and verifiable computation.ZKPs enable one party (a prover: P) to prove to another (a verifier: V) that a statement is true or correct without revealing any additional information.This powerful capability has led to ZKPs being applied and proposed for application in blockchain technologies, verifiable machine learning, and electronic voting.However, ZKPs have yet to see widespread, ubiquitous adoption due to the exceptionally high computational complexity of the proving process.Naturally, there has been recent work to accelerate ZKP primitives and protocols using GPUs and ASICs.However, the protocols considered so far face one of two challenges: they require a trusted setup for each new application or generate large proofs with high verification costs, limiting their applicability in scenarios with numerous verifiers or strict verification time constraints.HyperPlonk is a state-of-theart ZKP protocol that supports both one-time, universal setup and small proof sizes/verification costs expected by publicly verifiable, consensus-based systems (e.g., blockchain).While HyperPlonk's setup and verifier properties are highly desirable, the proving phase is costly.A HyperPlonk prover must compute on large bitwidths (e.g., 255-381b) and polynomials (e.g., of degree 2 24 ), employs computationally (e.g., MSM) and bandwidth (e.g., SumCheck) intensive kernels, and the complete protocol comprises many steps, each constituting distinct kernels.We present an accelerator, zkSpeed, to

Alex B. Grilo, Philippe Lamontagne

The round complexity of interactive proof systems is a key question of practical and theoretical relevance in complexity theory and cryptography. Moreover, results such as QIP = QIP(3) (STOC'00) show that quantum resources significantly help in such a task. In this work, we initiate the study of round compression of protocols in the bounded quantum storage model (BQSM). In this model, the malicious parties have a bounded quantum memory and they cannot store the all the qubits that are transmitted in the protocol. Our main results in this setting are the following: 1. There is a non-interactive (statistical) witness indistinguishable proof for any language in NP (and even QMA) in BQSM in the plain model. We notice that in this protocol, only the memory of the verifier is bounded. 2. Any classical proof system can be compressed in a two-message quantum proof system in BQSM. Moreover, if the original proof system is zero-knowledge, the quantum protocol is zero-knowledge too. In this result, we assume that the prover has bounded memory. Finally, we give evidence towards the “tightness” of our results. First, we show that NIZK in the plain model against BQS adversaries is unlikely with standard techniques. Second, we prove that without the BQS model there is no 2–message zero-knowledge quantum interactive proof, even under computational assumptions.

Lior Rotem

The seminal work of Goldreich and Krawczyk (SIAM Journal on Computing) shows that any constant-round public-coin interactive proof for languages not in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mi mathvariant="sans-serif">B</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> </mml:mrow> </mml:mrow> </mml:math> cannot be black-box zero knowledge. Their result says nothing, however, about proofs (or arguments) of knowledge for languages in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mi mathvariant="sans-serif">B</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> </mml:mrow> </mml:mrow> </mml:math>. As a special case, their work leaves open the question of whether Schnorr's protocol for proving knowledge of discrete logarithms in cyclic groups is black-box zero knowledge. In this work we focus on the zero knowledge of proofs of knowledge, centering on Schnorr's protocol as a prominent example. We prove two lower bounds, ruling out two different classes of simulators through which Schnorr's protocol can be proven zero knowledge: We prove that if a relation <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>ℛ</mml:mi> </mml:mrow> </mml:math> has a public-coin interactive proof of knowledge that is black-box zero knowledge and this protocol is compatible with the Fiat-Shamir transform in the random oracle model, then <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>ℛ</mml:mi> </mml:mrow> </mml:math> must be efficiently searchable. As an immediate corollary, we deduce that Schnorr's protocol cannot be black-box zero knowledge in groups in which discrete log is hard. We define a new class of simulators for Schnorr's protocol, which we call generic simulators. A generic simulator is one that works in any cyclic group, and does not use the representation of the specific group in which Schnorr's protocol is instantiated. We prove that Schnorr's protocol cannot have generic simulators. As an additional contribution, we generalize the original lower bound of Goldreich and Krawczyk, to prove that a language not in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mi mathvariant="sans-serif">B</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> </mml:mrow> </mml:mrow> </mml:math> cannot have an interactive proof (not necessarily of knowledge) that is both black-box zero knowledge and compatible with the Fiat-Shamir transform in the random oracle model. In conjunction with recent works, this extends the Goldreich-Krawczyk lower bound to public-coin protocols that are not constant-round but have round-by-round soundness, including the parallel repetition of any public-coin interactive proof.