This study focuses on the core needs of consumer data privacy protection in the context of the digital economy and creates a blockchain-based privacy and security architecture. Through a layered design, this architecture effectively combines data collection, blockchain core, privacy computing, smart contracts, and application integration modules. It integrates key techniques such as zero-knowledge proofs, homomorphic encryption, and decentralized identity to ensure that data is encrypted and stored throughout its creation and destruction, implements meticulous access rights management, and implements a verifiable audit process. The dataset used in this experiment is the 2024 CMS market county-level administrative district public dataset in the United States. In an environment simulating actual business pressures, the privacy protection effectiveness, system scalability, and computational and storage costs of this proposed system are tested. Comparisons are made with two typical implementations. While ensuring differential privacy and k-anonymity, the proposed system improves data transmission speed, reduces processing latency, and reduces storage consumption. This demonstrates the potential and superior performance of this system across multiple entities and industries. This study provides a practical and feasible technical implementation for blockchain-driven consumer data privacy protection and offers a verifiable engineering reference for data governance and cross-industry data sharing in the United States.
Yan Watequlis Syaifudin, Vipkas Al Hadid Firdaus, Imam Fahrur Rozi, Chandrasena Setiadi · 8 authors
The digitization of health records has enhanced clinical efficiency, but amplified risks related to data privacy, integrity, and auditability.While permissioned blockchains offer immutability and traceability, they often fail to reconcile transparency with confidentiality-either exposing sensitive data or obscuring it beyond regulatory scrutiny.To address this gap, this paper presents an integrated framework that combines Zero-Knowledge Proofs (ZKPs) with a permissioned blockchain to enable verifiable yet private healthcare transactions.A visit centric Electronic Health Record (EHR) model supports three real-world use cases: medication validity, procedure confirmation, and demographic verification.A four-layer architecture decouples data, application logic, cryptographic trust, and audit logging, allowing end-to-end validation without raw data disclosure.Experimental evaluation across three ZKP libraries (snarkJS, ZoKrates, and gnark) on a synthetic dataset of 1,000 patient visits demonstrates sub-500 ms verification latency, with snarkJS selected for its ecosystem compatibility despite slower raw performance.End-to-end pipeline latency averages 1.35 s, confirming feasibility for batch workflows such as insurance claims.The system further includes a web-based auditor interface that validates tamper-evidence under off-chain attacks, bridging cryptographic guarantees with operational compliance.
The rapid development of the Internet of Medical Things (IoMT) has also facilitated real-time monitoring of healthcare, yet creates major issues of security, privacy, and interoperability, particularly in terms of emerging threats of quantum computing. This paper introduces a quantum-resilient blockchain paradigm, which combines post-quantum cryptography (PQC), Zero Knowledge Proofs (ZKPs), and Fast Healthcare Interoperability Resources (FHIR) into secure and interoperable healthcare data management. Key encapsulation is performed using lattice-based algorithms, including Kyber and NTRU, and Dilithium and Falcon are algorithms used to secure digital signatures against quantum attacks. An authentication system which is based on a ZKP, and role-based access control allows privatizing access to electronic health records without exposing sensitive data. The framework is deployed on a PBFT-based permissioned blockchain and tested in simulated IoMT settings and has low latency, high throughput, and efficient cryptographic performance. In general, the suggested system will provide a reconfigurable, secure, and future-oriented method to safeguard the healthcare information against quantum threats without compromising the interoperability of the heterogeneous systems.
Open access
Cryptography and Data Security
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security
Compression algorithms and functions have been extensively utilized in various applications, e.g., in digital storage and communication. In recent years and with the popularity of machine learning applications, researchers have utilized compression techniques for addressing key problems in machine learning, e.g., for compressing artificial neural networks or for optimizing KV-cache memory in LLMs. Due to extensive applications of compression algorithms in different domains, a whole new era of innovations and applications for data compression algorithms can be envisioned. In this article, we discuss that compression functions with interesting properties, e.g., fully homomorphic compression (FHC) algorithms, can have applications beyond compressing data. FHC algorithms can potentially enable performing computation on compressed (and encrypted) data. Thus, fully homomorphic compression techniques can be used for reducing the computational and communication costs of compute and communication-intensive workloads, such as fully homomorphic encryption (FHE) & zero-knowledge proof (ZKP) applications, (secure) vector databases (VDBs and SVDBs), blockchain-based technologies, image and video processing, privacy-preserving or private LLMs, and LLM & AI inference, etc.
The secure, privacy-preserving sharing of genomic data across multiple institutions is a critical enabler for precision medicine, yet it remains fundamentally constrained by the identifiability and immutability of genomic data. While blockchain technologies have been proposed to provide decentralized governance, auditability, and tamper resistance for genomic data sharing, blockchain-only solutions are insufficient because they expose transaction metadata, access patterns, and smart-contract logic, leaving significant privacy risks unresolved. Zero-Knowledge Proofs (ZKPs) have recently emerged as a key cryptographic primitive for addressing such limitations, enabling verifiable access control, policy compliance, and computation correctness without disclosing sensitive genomic data. Although several surveys examine ZKPs or blockchain in isolation or across heterogeneous application domains, there is currently no dedicated survey that systematically analyzes their combined use in multi-party blockchain-based genomic data sharing systems. This paper addresses this gap by presenting a comprehensive, domain-specific survey of ZKP-enabled blockchain architectures for genomic data sharing. We classify existing approaches by architectural models, ZKP techniques, governance mechanisms, and threat-mitigation capabilities, and then compare their assumptions, performance characteristics, and deployment maturity. Furthermore, we identify open challenges in scalability, interoperability, proof overhead, and regulatory compliance, and outline future research directions for secure, scalable, and ethically compliant genomic data-sharing ecosystems.
Abstract Bilinear pairings have emerged as a fundamental tool in public-key cryptography, enabling advanced protocols such as identity-based encryption, short signatures, and zero-knowledge proofs. This paper focuses on optimizing pairing computations on curves with embedding degree 2, addressing both theoretical foundations and practical implementations. We propose an optimized double-and-add ladder algorithm that leverages the technique of y -coordinate recovery, achieving superior performance for the Tate pairing on supersingular curves and the Omega pairing on non-supersingular curves. Our method is implemented based on the RELIC cryptographic library, demonstrating significant efficiency improvements over Miller’s algorithm. Specifically, it reduces the number of base field multiplications (respectively CPU clock cycles) by 17.53 % (respectively 13.58 %) for the reduced Tate pairing on supersingular curves with a 1536-bit field size and by 12.37 % (respectively 8.39 %) for the Omega pairing on non-supersingular curves of the same size. This work establishes the first comprehensive implementation framework for cubical-based pairing computations on curves with embedding degree 2, providing quantified optimizations for practical cryptographic deployment.
Hyeonbum Lee, Seunghun Paik, Hyunjung Son, Jae Hong Seo
An inner product argument (IPA) is a cryptographic proof system that serves as a fundamental building block for various applications, such as zero knowledge proofs and verifiable computation. Bulletproofs (IEEE S&P 2018), a well-known IPA under the discrete logarithm (DL) assumption, features a short, logarithmically-sized proof, making it suitable for blockchain applications. However, its major drawback is the linear verifier cost (O(N)), which presents a significant bottleneck in settings like verifiable computation. To address this, recent advancements have successfully reduced the verification complexity to square-root order (O(√N)) under the same assumption (e.g., Asiacrypt 2022, IEEE TIFS). In thiswork, we propose Cougar, a novel IPAthat breaks this square-root barrier to achieve an unprecedented cubic-root verifier complexity (O(3√N)), while strictly maintaining the compact logarithmic proof size (O(logN)) characteristic of Bulletproofs. To achieve this, Cougar introduces a generalized two-tier commitment framework combined with adisjoint interpolationstrategy for efficient consistency checks. We implemented Cougar in Rust and performed a comprehensive benchmarking against Bulletproofs and Leopard (IEEE TIFS). Our evaluation demonstrates that while Cougar incurs a moderate increase in prover overhead, its verification time scales significantly better for large instances. Concretely, for a witness size ofN= 220, Cougar achieves a 50× verification speed-up over Bulletproofs and exhibits a superior asymptotic growth rate compared to existing sublinear IPAs.
Open access
Cryptography and Data Security
Physical Unclonable Functions (PUFs) and Hardware Security
Nishanth Shet, R. Chinmai, Preethi Preethi, Y. V. Srinivasa Murthy
Abstract As quantum computing grows, the security of RSA and ECC offers is becoming increasingly flush. A novel Quantum Resistant Multipath CryptoGraph protocol (QR-MCP) has been proposed in this work, which is a multi-layered security framework that combines lattice-based cryptography, SPHINCS+ post-quantum signatures, onion routing, with AI-driven anomaly detection for long lifetime security and privacy of data. Encrypting messages in multiple paths increases security as larger network attackers cannot intercept an entire message. Ledgering on the blockchain is also used for integrity verification for the protocol, and the protocol also uses AI models to detect anomalies in real-time. QR-MCP has shown to be resilient to simulated cyber attacks such as man-in-the-middle, traffic analysis as well as collusion based decryption. Future scalability to new threats will gain strength with the introduction of homomorphic encryption and zero-knowledge proof (ZKP).
Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) have emerged as a critical technology for privacy-preserving computation and blockchain applications. However, systematic performance analysis of practical implementations remains limited, hindering informed technology adoption decisions. This study presents a comprehensive benchmarking analysis of the Groth16 protocol implementation using the widely-adopted Circom-snarkjs framework. We developed an automated benchmarking platform that systematically measures performance across seven representative circuit types with varying computational complexity (1-11 R1CS constraints). Our methodology ensures reproducible measurements through controlled experimental design with statistical validation. The platform captures detailed metrics for all three phases of the Groth16 protocol: witness generation, proof creation, and verification. Results from 35 independent measurements reveal several important findings. Witness generation demonstrates consistent performance across circuit types, averaging 57.6±12.1 milliseconds. Proof generation times range from 832 to 1,147 milliseconds, showing non-linear scaling with circuit complexity. Verification times remain relatively stable (741-884 milliseconds), confirming Groth16's theoretical constant-time verification advantage. All measurements achieved 100% success rate with complete proof validation. Notably, circuit structure significantly impacts performance beyond simple constraint counting. Comparison-based circuits achieve 13.22 constraints per second efficiency, substantially outperforming arithmetic circuits (1.02-4.36 constraints/second). This finding provides actionable guidance for circuit design optimization. The study contributes an open-source benchmarking framework for reproducible zk-SNARK research and provides empirical performance data for technology adoption decisions. Our findings support the practical deployment of Groth16 for applications requiring efficient zero-knowledge proofs while highlighting optimization opportunities for circuit designers.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
Traditional and electronic voting systems face significant challenges in ensuring transparency, security, and voter trust. Issues such as centralized control, lack of auditability, vulnerability to tampering, and potential for fraud undermine the integrity of electoral processes. This paper proposes a novel blockchain-based electronic voting system designed to address these shortcomings through decentralized ledger technology and smart contracts. The system ensures vote integrity, voter anonymity, and public verifiability while preventing double voting and eliminating single points of failure. By employing cryptographic techniques such as zero-knowledge proofs and ring signatures, voter privacy is maintained without compromising transparency. The proposed architecture is evaluated through simulation, demonstrating scalability, reduced transaction costs, and robustness against common cyber threats. This work contributes to the advancement of trustworthy digital democracy and provides a feasible framework for real-world electoral deployment.
The concept of blockchain has transformed the trust concept by decentralizing, non-modifiable, and transparent, but there is a certain conflict between the principle of public verifiability and data privacy. As DeFi and cross-institutional data collaboration should grow, it has become a fundamental concern to have the confidentiality of this data without losing verifiability on-chain. The following paper will be a review of blockchain privacy technologies developed in 2020-2025, which will involve the history of zero-knowledge proofs and homomorphic encryption development at the cryptographic primitive level, as well as share new developments such as secure multi-party computation. It points out advances in recursive proof systems, distributed proof generation architectures and scalable multi-party computing systems to overcome bottlenecks in performance. There is a trade-off between privacy, system performance, regulatory compliance, and decentralization in a comparative analysis of technology integration in both public and permissioned chains. Lastly, research directions in the future are suggested in order to overcome issues associated with low proof efficiency, regulatory compliance problems, and migration of post-quantum cryptography. The review offers both theoretical and technical sources on how to develop trusted blockchain infrastructure that would strike the right balance between compliance, high-performance, and data sovereignty.
Advancements in networking applications increase the requirement for secure data storage and an efficient data access mechanism with robust networking characteristics. Consequently, the huge volume of data generated from the het-erogeneous networks, such as smart cities, healthcare, and smart energy trading systems, suffers from scalability issues and generates insights for secure data storage and effective data management. Therefore, the research proposes a secure data storage and access scheme named Multimodal Biometric-enabled Zero-Knowledge Proof of Stake(MBZKPS). The Multimodal Biometric Data Access(MBDA) ensures secure and robust access to the heterogeneous data with reduced computational overhead. The Distributed Storage System and the Zero Knowledge Protocol with Proof of Stake alleviate the storage pressure on the blockchain and regulate the heterogeneous data storage and access in the blockchain. The Message Digest 5(MD5) with Homomorphic Encryption enables computations on the encrypted data with better data confidentiality preserva-tion. The introduction of the blockchain eliminates the scalability issues with improved privacy preservation and data integrity. Simulation results validate the superiority of the MD5 with Homomorphic Encryption (HE) used in research by achieving 0.95ms decryption time, and 0.97 encryption time with 0.73 Genuine User Rate occupying 363.76KiloBytes of memory for 250 nodes. In addition, the proposed research performs secure data storage with a 1025.85 ms response time and 1.01ms transaction time using blockchain.
We present CHRONOS, the first autonomous AI agent that simultaneously achieves plaintextblindness (all data is processed under fully homomorphic encryption without ever beingexposed), cryptographically enforced time bound existence (the agent’s own decryption key islocked behind a publicly verifiable proof of sequential work, rendering it inaccessible until aprecise future moment), and remote verifiability of self destruction (a zero knowledge proofcertifies that the key material has been irreversibly destroyed after mission completion). Theagent’s operational lifespan is governed by a “cryptographic fuse” constructed from a proof ofsequential work (PoSW) whose computation time accurately matches the intended missionduration. A drand decentralized randomness beacon serves as a trusted time oracle to trigger thefinal key shredding. Crucially, the erasure proof is a non interactive zero knowledge argument(SNARK) that proves the correct execution of the entire self destruction sequence—including thePoSW solution, decryption of the private key, and subsequent memory zeroization—enablingany third party to cryptographically verify the agent’s annihilation without trusting the agent orits hardware. We provide a complete system architecture, a formal security model with gamebased definitions and reductions to standard assumptions, and a proof of concept implementationusing Zama’s TFHE rs for encrypted inference, a Cohen Pietrzak PoSW implementation, and aGroth16 SNARK. Our benchmarks indicate that FHE inference on a small neural network (50 Kparameters) completes in seconds, the PoSW background thread consumes negligible resources,and the erasure proof can be generated and verified in under three seconds. CHRONOSrepresents a fundamental advance in secure, disposable AI agents, with immediate applications indefense, intelligence, and high privacy environments.
Card-based zero-knowledge proof (ZKP) protocols allow a prover to convince a verifier that it knows a witness of a given statement, without revealing any information, using a physical deck of playing cards. Previous studies have focused on puzzles with a specific connected component, such as a simple cycle and a polyomino. In this study, we propose a unified approach to handle a family of connected components, including a tree, path, cycle, and polyomino. This approach achieves this verification in O(mn) steps relative to a given grid size m × n. Using this approach, we construct a card-based ZKP protocol for Nurimeizu, where the goal is to find the shortest path on a given grid.
This paper analyzes the shortcomings of traditional authentication mechanisms in web applications operating over the secure TLS 1.3 protocol. It is established that even with an encrypted channel, the transmission of secret data (passwords, tokens) remains a primary attack vector. An improved protocol is proposed that integrates an authentication mechanism based on zero-knowledge proofs (zk-SNARK) immediately after session establishment via Elliptic Curve Diffie-Hellman (ECDHE) key exchange. This approach completely eliminates the transmission of client credentials, significantly increasing resistance to phishing and server database compromises.
Oracles have become a foundational component of decentralized finance and cross-chain systems by enabling smart contracts to consume external data such as price feeds, timestamps, and event confirmations. However, oracles are fundamentally limited to validating facts and cannot determine whether a transaction or state transition is legally, contractually, or behaviorally permitted. As regulatory regimes such as the European Union’s Markets in Crypto-Assets Regulation (MiCA) impose enforceable obligations on token issuers, service providers, and infrastructure operators, this limitation creates a critical enforcement gap. This paper introduces a Logic Validation Layer (LVL), implemented via the Crystal Validator™, which enforces jurisdictional, behavioral, and policy-based constraints directly within token execution paths. By separating factual data delivery, cross-chain transport, and logic enforcement into distinct architectural layers, the proposed model enables deterministic compliance without sacrificing interoperability, composability, or performance. The paper argues that while oracles remain necessary, logic-level validation has become unavoidable for regulated cross-chain finance.
Zero-knowledge proof is a special cryptographic technique that allows a prover to convince a verifier about the correctness of a claim without explicitly disclosing the claim itself. With the advancements of blockchain technologies, zero-knowledge proof has been successfully integrated into many decentralized applications over the years. ZoKrates, with its ease-of-use and direct integration to blockchain platforms, has emerged as a leading framework for developing, generating and verifying zero-knowledge proofs. This survey compiles a corpus of 347 documents that cite the original research work of ZoKrates by considering the period ranging from 2018 to 2025. Out of this corpus, this survey systematically selects and analyzes a total of 87 different documents including only peer-reviewed publications and excluding the gray literature. To the best of our knowledge, this is the first survey in the literature to follow a systematic approach to analyze the privacy- preserving applications in blockchain from the perspective of ZoKrates. This survey presents three different classifications over the documents with respect to (i) the applications they develop, (ii) the challenges they frequently encounter and (iii) the metrics they often use to measure performance of their techniques. Based on the challenges identified, this survey finally discusses numerous future research directions to promote potential advancements in the field and attract the attention of scientific and industrial communities. Feedback from readers regarding any inaccuracies or misinformation in this survey is welcome.
Insurance operations generate continuous streams of regulated state transitions-policy issuance, claim adjudication, premium collection, broker remittance-that must be auditable for years and verifiable on demand by regulators, reinsurance counterparties, and litigation adversaries. The prevailing industry practice protects these audit trails through database access controls and policy-based logging in mutable relational stores. This approach is insufficient: it requires regulators to trust the platform vendor, exposes Personally Identifiable Information (PII) during inspection, and provides no mathematical defense against retrospective tampering by privileged insiders or attackers with database access. This paper introduces the Regure Immutable Audit (RIA) Protocol, a cryptographic statetransition anchoring system that organizes insurance operational events into per-tenant Merkle trees, signs each daily root with a tenant-specific hardware-backed key via AWS Key Management Service, and anchors the signed root to two independent immutable witnesses: AWS S3 Object Lock and the Bitcoin blockchain via OpenTimestamps. Verification is implemented as a zero-knowledge protocol: an external auditor can verify the cryptographic integrity of any specific event in any specific claim using a Merkle proof of length 𝑂(log 𝑛)against a publicly anchored root, without ever observing the underlying claim data. We provide formal definitions of the State-to-Hash Mapping, the Hash-Linked Lifecycle property, and the Dual-Witness Anchoring Construction. We prove that the system is tamper-evident under standard cryptographic assumptions, that verification has logarithmic complexity in the number of events per tenant per day, and that the Zero-Knowledge Audit property holds against both honest-but-curious regulators and an actively malicious platform vendor. We describe the production implementation deployed in Cryptographic State-Transition Anchoring Piyoosh Rai P a g e | 2 Regure, including the integration with AWS KMS for tenant-isolated signing keys and the dual anchoring path through Object Lock storage and Bitcoin transaction confirmation. We discuss the implications for Continuous Assurance under DORA Article 12, the Swiss Federal Act on Data Protection (FADP), the Saudi Arabian Monetary Authority (SAMA) Cyber Security Framework, and Lloyd's market reporting requirements for delegated authority operations. The RIA Protocol moves the insurance industry's audit trust model from "trusting the vendor" to "trusting the math"-a structural shift that resolves the long-standing conflict between the regulatory Right to Audit and the data subject's right to privacy.
Decentralized exchanges (DEXs) have emerged as a foundational component of blockchain-based financial systems, enabling trustless asset trading without centralized intermediaries. However, the transparency of public mempools introduces significant vulnerabilities, including front-running, sandwich attacks, transaction reordering, and broader information asymmetry. In response, Cryptographic mechanisms such as Zero Knowledge (ZK) based architectures and commit reveal schemes are increasingly proposed as a solution to these vulnerabilities. This research systematically reviews the structural transparency paradox and cryptographic architectures in Decentralized Exchange based Automated Market Makers (DEX-AMM), evaluate their effectiveness in mitigating Maximal Extractable Values (MEVs), analyze computational complexity trade-offs including proof generation/verification costs, gas overhead, latency, and throughput, and identify why commit-reveal may offer superior practical viability despite zk-proofs' stronger theoretical privacy guarantees. A comprehensive search was conducted across arXiv, IEEE Xplore, ACM Digital Library, Scopus, Web of Science, Google Scholar including grey literatures for studies published between 2021 to 2026. Findings indicate that ZK-based approaches provide strong cryptographic privacy guarantees but often incur computational overhead and integration complexity, zk-rollups provide strong validity guarantees through cryptographic proofs, but their practical security depends heavily on the sequencer layer used by ( zkSync, StarkEx, and Loopring) which is responsible for transaction ordering, which can censor, delay, reorder transactions or cause failure of execution, while Commit-reveal schemes may be superior for real-world DEXs due to their constant time hash-based complexity (O(1)), lower gas costs, sub-second latency, and simpler implementation, despite requiring two-transaction UX friction, which can be mitigated through wallet automation. The computational efficiency advantage of commit-reveal becomes critical as DEX transaction complexity increases, where zk-circuit depth grows exponentially. Future research should prioritize optimizing zk-circuit efficiency, developing zk-commit-reveal hybrids system that balance cryptographic strength with computational practicality, and advancing hash-based commit-reveal schemes with UX improvements. DEX developers should prioritize commit-reveal for latency-sensitive applications and zk-proofs only when strongest cryptographic privacy is mandatory.
<b><i>Zero-knowledge proof (ZKP) systems</i></b> such as<b><i> zk-SNARKs</i></b> and<b><i> zk-STARKs</i></b> are increasingly promoted as comprehensive solutions for privacy, scalability, and selective disclosure in blockchain-based systems. While these cryptographic primitives provide strong guarantees regarding computational correctness and data confidentiality, they are frequently mischaracterized as substitutes for regulatory compliance, legal enforceability, or supervisory control mechanisms. This paper presents a structural and functional comparison between zero-knowledge proof systems and the Crystal Validator™ (CV), a logic-layer enforcement architecture designed to encode and enforce jurisdiction?aware regulatory requirements. We demonstrate that cryptographic validity proofs are orthogonal to—and insufficient for—legal compliance, accountability, and regulatory supervision as required under frameworks such as the EU Markets in Crypto-Assets Regulation (MiCA). We argue that regulatory enforcement logic must exist above cryptographic proof layers and cannot be replaced by them without introducing systemic compliance risk.
This paper presents a zero-knowledge credential framework for secure and privacy-preserving attribute verification across multiple independent systems. The framework enables users to prove statements about their attributes without revealing the underlying values, while preventing cross-domain tracking by eliminating globally stable identifiers. The construction combines commitment schemes, digital signatures, zero-knowledge proofs, scoped pseudonyms, and accumulator-based revocation into a unified and modular design. Scoped identifiers ensure that user activity cannot be linked across different verification domains, while predicate proofs allow verification of conditions such as threshold checks without disclosing sensitive data. Revocation is supported through an efficient accumulator mechanism that enables verification without revealing credential identities and without increasing cost with the size of the revoked set. The system follows a complete lifecycle including credential issuance, proof generation, verification, and revocation checking. All proofs are non-interactive and bound to verifier-specific challenges, ensuring resistance to replay attacks. Security is based on standard cryptographic assumptions, providing guarantees for attribute privacy, proof soundness, unlinkability, and resistance to collusion. Experimental evaluation demonstrates that the framework achieves practical performance, with low verification latency, compact proof size, and stable scalability. The results show that strong privacy, verifiable authenticity, and efficient revocation can be achieved simultaneously without relying on trusted setup or pairing-based cryptography. The modular structure further supports integration with decentralized identity systems and real-world deployment scenarios.