Zero-Knowledge Proofs (ZKP) and Homomorphic Encryption (HE) are crucial for data privacy in applications like cloud, blockchain, and analytics. However, the real-world adoption often faces performance challenges, particularly in the execution of the Number Theoretic Transform (NTT) required for polynomial multiplication involving sizes beyond \(2^{20}\) and large integer widths (e.g., 256 bits). FPGAs offer a promising platform for acceleration, but efficiently implementing large-size NTTs remains difficult due to the limited on-chip resources. The widely adopted four-step NTT method, used to relieve the need for large on-chip memory, introduces performance bottlenecks. Initially, the traditional dataflow NTT architecture may not fully exploit available compute capability, which hinders achieving peak performance. Furthermore, during the matrix transpose phase, the non-sequential access to external High-Bandwidth Memory (HBM) causes inefficiency. To address these challenges, we introduce HiFA, an FPGA-based automatic accelerator framework designed for high-performance and flexible large-size NTT computations. HiFA utilizes a stacked NTT architecture for high parallelism, maximizing HBM throughput. It supports various decomposed polynomial sizes via a novel reordering module. Additionally, a specialized cyclic shuffle module is integrated to optimize data movement during the matrix transpose step, alleviating random memory access delay. HiFA also provides an automatic Design Space Exploration (DSE) framework that identifies optimal four-step decomposition parameters and generates corresponding hardware configurations. Our experiments show that the FPGA implementation of HiFA achieves an average speedup of 2.97× and up to 7.25× improvement in latency over prior state-of-the-art FPGA solutions. Compared to prior GPU-based methods, HiFA achieves an average energy efficiency gain of 2.24×.
This paper investigates performance bottlenecks of consortium blockchains under high-throughput and low-latency requirements, focusing on excessive storage burden on full nodes and redundant computation in transaction validation. Based on consortium blockchain, a novel architecture named Server-Side Core Chain (SSC) is proposed. In this architecture, the core functions of blockchain ledger data storage and smart contract execution are delegated from decentralized consensus nodes to a server cluster jointly managed and trusted by consortium members. The consensus node layer is restructured into a lightweight ``Consensus and Audit Network,” dedicated to transaction ordering and state commitment verification. This paper elaborates on the design principles, operational workflow, and security model of the SSC architecture. Theoretical analysis and prototype experiments demonstrate that the architecture significantly enhances the transaction processing capacity of consortium blockchains (experimental results show a throughput improvement of more than 18 times), greatly reduces the entry barriers and operational costs for member nodes (storage overhead reduced by over 99%), and ensures the verifiability of off-chain computations and data privacy through cryptographic commitments and zero-knowledge proofs [1]. The SSC architecture offers a new solution for deploying consortium blockchains in large-scale applications, including finance, supply chain management, and e-government.
R. Suganya, P. J. Sidharth, C. Vinston Jose, P. R. Lighittha · 6 authors
This chapter explores the integration of blockchain technology and intelligent automation to address long-standing challenges in the global blood supply chain (BSC). The BSC is frequently plagued by fragmentation, traceability gaps, logistical inefficiencies, and compliance hurdles, all of which compromise patient safety and operational efficiency. By combining permissioned blockchains with smart contracts, Internet of Things (IoT) sensors, federated learning, and zero-knowledge proofs (ZKPs), this chapter proposes a modular architecture—BloodChain—that enhances transparency, automation, and data privacy across the supply lifecycle. Experimental implementations demonstrate improved traceability, predictive analytics, and compliance with privacy regulations such as GDPR and HIPAA. The chapter concludes with a discussion on interoperability, governance, and future research directions, offering a blueprint for secure, scalable, and intelligent blood logistics in digital healthcare ecosystems.
FibRace, jointly developed by KKRT Labs and Hyli, was the first large-scale experiment to test client-side proof generation on smartphones using Cairo M. Presented as a mobile game in which players proved Fibonacci numbers and climbed a leaderboard, FibRace served a dual purpose: to engage the public and to provide empirical benchmarking. Over a three-week campaign (September 11-30, 2025), 6,047 players across 99 countries generated 2,195,488 proofs on 1,420 unique device models. The results show that most modern smartphones can complete a proof in under 5 seconds, confirming that *mobile devices are now capable of producing zero-knowledge proofs reliably*, without the need for remote provers or specialized hardware. Performance was correlated primarily with RAM capacity and SoC (System on Chip) performance: devices with at least 3 GB of RAM proved stably, when Apple's A19 Pro and M-series chips achieved the fastest proving times. Hyli's blockchain natively verified every proof onchain without congestion. FibRace provides the most comprehensive dataset to date on mobile proving performance, establishing a practical baseline for future research in lightweight provers, proof-powered infrastructure, and privacy-preserving mobile applications.
The security and privacy of vehicle-to-everything (V2X) communication are critical for the reliability of future intelligent transportation systems (ITS). Existing V2X public key infrastructure (VPKI) models face centralization risks, inefficient revocation, limited privacy, and vulnerability to quantum attacks. While blockchain-based frameworks improve decentralization, they often depend on classical cryptography and offer limited defense against Sybil attacks and identity linkage. This paper presents DIMA, a post-quantum decentralized identity management architecture for V2X authentication and privacy preservation. DIMA integrates a dual-layer permissioned blockchain with CRYSTALS-Dilithium for quantum-resistant digital signatures, zk-STARKs for anonymous pseudonym issuance, and privacy tokens with a reputation-based refresh mechanism for Sybil resistance. A hash-based accumulator supports scalable revocation, while self-sovereign identity (SSI) and zero-knowledge attribute proofs enable privacy-preserving access control. Security is analyzed under a quantum-capable adversarial model, and performance is evaluated using analytical benchmarks. Results demonstrate that DIMA achieves strong unlinkability, scalable Sybil deterrence, and real-time authentication, addressing key limitations of prior approaches and providing a quantum-resilient foundation for next-generation V2X ecosystems.
Tuan-Dung Tran, Huynh Phan Gia Bao, Tra Minh Trong, Nguyen Tan Cam · 5 authors
Integrating decentralized identity (DID) systems with state authorities introduces complex challenges related to trust, privacy, and auditability. The Lotus Bridge framework addresses these by proposing a hybrid digital identity architecture suitable for national-scale deployment. It integrates a permissioned Proof-of-Authority (PoA) blockchain for sovereign credential issuance with a cross-chain verification bridge that utilizes zero-knowledge proofs to enable privacy-preserving selective disclosure. This architecture is one of the first to combine state-backed issuance with interoperable, private cross-chain verification in a unified system. Two core protocols—state-anchored issuance and cross-chain verification—are formally defined and implemented in a working prototype. Experimental results demonstrate strong performance: cryptographic proofs remain under 600 bytes and end-to-end verification latency consistently stays below 2 seconds, enabling real-time applicability. Additionally, parallelization reduces proof generation time by over 90%, and the system achieves significant cost efficiency, with on-chain verification starting at 244 Gwei per credential and scaling to 14K Gwei for 1,000, offering up to 75% cost savings compared to existing Ethereum and Polygon solutions. These findings establish Lotus Bridge as a scalable and costeffective foundation for sovereign digital identity in cross-chain ecosystems.
The rapid rise of generative AI has made secure and scalable prompt engineering more important than ever. But there’s a catch — prompts often carry sensitive, proprietary, or regulated information, which brings real security and privacy risks. In response, our research presents a blockchain-powered framework designed for confidential prompt sharing. It brings together smart contracts, zero-knowledge proofs (ZKPs), and a hybrid consensus model that blends Proof-of-Stake with Byzantine Fault Tolerance (PoS-BFT). This combination doesn’t just enhance security — it also boosts energy efficiency, scalability, and resilience. When benchmarked against platforms like Ethereum and Hyperledger Fabric, our framework delivered lower latency, better performance, and strong reliability even under adversarial conditions. Plus, it’s built to work handin-hand with agentic AI workflows and decentralized identity systems, offering a flexible, futureready foundation for secure collaboration between AI agents.
The growing reliance on digital financial services necessitates a secure, efficient, and privacy-centric approach to identity verification and Know Your Customer (KYC) compliance. Traditional identity management systems rely on centralized databases, making them susceptible to data breaches, inefficiencies, and regulatory constraints. Over 10 billion identity records have been exposed in centralized KYC breaches, leading to a 60% increase in financial fraud cases. The rise of Decentralized Finance (DeFi) has further complicated KYC compliance, requiring innovative solutions that balance privacy and regulatory requirements. This paper proposes a Web3-powered decentralized identity framework that leverages blockchain technology, self-sovereign identity (SSI), verifiable credentials (VCs), and zero-knowledge proofs (ZKPs). By eliminating reliance on centralized authorities, our system enhances data privacy, reducing personally identifiable information (PII) disclosure by 80% while ensuring compliance with AML and GDPR regulations. The integration of zk-SNARKs enables trustless identity verification with an average proof generation time of 12.5 seconds, significantly reducing the 3–5 day verification period required by traditional systems. Smart contract-based KYC automation eliminates intermediaries, cutting compliance costs by 40% and reducing fraud risk by 60%. Through comparative analysis, we highlight that decentralized KYC improves security, cost-effectiveness, and scalability compared to traditional models. Performance evaluation confirms that transaction throughput remains within acceptable blockchain limits, with gas costs stabilized at 35,000–55,000 Gwei per verification request. Despite challenges in regulatory adaptation and zk-SNARK scalability, the proposed model demonstrates the feasibility of Web3-driven identity management for trustless, privacy-preserving, and compliant financial ecosystems.
Fernando Castillo, Eduardo Brito, Sebastian Werner, Pille Pullonen · 5 authors
Service Level Agreement (SLA) monitoring in service-oriented environments suffers from inherent trust conflicts when providers self-report metrics, creating incentives to underreport violations. We introduce a framework for generating verifiable SLA violation claims through trusted hardware monitors and zero-knowledge proofs, establishing cryptographic foundations for genuine trustworthiness in service ecosystems. Our approach starts with machine-readable SLA clauses converted into verifiable predicates and monitored within Trusted Execution Environments. These monitors collect timestamped telemetry, organize measurements into Merkle trees, and produce signed attestations. Zero-knowledge proofs aggregate Service-Level Indicators to evaluate compliance, generating cryptographic proofs verifiable by stakeholders, arbitrators, or insurers in disputes, without accessing underlying data. This ensures three security properties: integrity, authenticity, and validity. Our prototype demonstrates linear scaling up to over 1 million events per hour for measurements with near constant-time proof generation and verification for single violation claims, enabling trustless SLA enforcement through cryptographic guarantees for automated compliance verification in service monitoring.
The Monty-Hall (parameterized strategist-host) Theorem along with a constructive proof is presented, by solving the corresponding Monty-Hall Problem, wherein the host plays a parameterized strategy on the guest. It establishes the limits on the range of values for the probability of winning the prize. Eight extreme strategies (corresponding to the set of extreme values for the three perturbation parameters) have been well characterized. It is shown that there does not exist any strategy wherein a switched-choice will always (irrespective of the placement of the prize and irrespective of the initial-choice of the guest) lead to an enhancement in the chances of winning the prize. The classical Monty-Hall Problem is a special case with zero-value for each of the three perturbation parameters. This paper is an attempt to correct the errors (of long-standing historical significance) in the application of statistical methodology in solving the classical Monty-Hall Problem - one of them being the erroneous use of conditional probabilities for updating the knowledge to facilitate the decision-making by the guest, based on the information about a losing-choice, which itself is dependent on the initial-choice of the guest. Similar scenarios in data science, machine learning & artificial intelligence can have serious far-reaching consequences.
Purpose: This paper formulates a new theoretical framework to address the principal-agent problem in representative democracy through a dynamic voting mechanism. Based on Rousseau’s concept of the general will and contemporary analyses of corporate influence in politics, I build a rigorous mathematical model that enables voters to maintain continuous oversight over their elected representatives. Design/methodology/approach: I developed a rigorous mathematical model integrating an anonymous blockchain-based voting system. This system allows voters or voter groups to continuously monitor their representatives while preserving their privacy through zero-knowledge proofs. The model uses game theory and extends Condorcet’s Jury Theorem to analyze voter behavior under dynamic oversight conditions. Findings: The results show that such a system can encourage a more responsible form of representative democracy while maintaining electoral stability. Detailed implementation architectures show that the model is not only theoretically rigorous but also practically feasible through advanced cryptographic tools. Practical implications: The proposed architecture enables real-time voter engagement without compromising privacy, providing a blueprint for secure, transparent, and scalable voting systems applicable in modern democratic systems. Originality/value: This research combines political theory, cryptographic system design, and social choice theory to propose a new paradigm for democratic governance. The integration of zero-knowledge proofs with dynamic feedback mechanisms offers a scalable solution to fundamental challenges of voter privacy and election integrity, with far-reaching implications for democratic theory and its practical application.
Xiangyun Tang, Minyang Li, Tao Zhang, Yijing Lin · 7 authors
In low-altitude networks, various aerial platforms such as unmanned aerial vehicles and airships cooperate to provide services including real-time monitoring, emergency response, and data collection. These platforms often operate with limited computing resources, restricted energy supply, and unstable wireless connectivity, making centralized data processing inefficient and prone to privacy risks. Federated Learning (FL) provides a promising solution by enabling multiple platforms to collaboratively train a shared model without exchanging raw data. However, the presence of Byzantine clients and a potentially malicious server poses serious threats to the robustness and trustworthiness of FL in such environments. Existing Byzantine-robust FL methods typically assume a semi-honest server and rely on auxiliary information such as clean datasets or known attacker ratios, which limits their applicability in dynamic and non-IID scenarios. In this paper, we propose zkFL, a Byzantine-robust FL framework that embeds zero-knowledge proofs to ensure verifiable aggregation under a malicious server. ZkFL allows clients to verify the correctness of server-side aggregation and dynamically adjusts client weights based on inference-guided detection, without relying on external datasets. Each round includes a zk-SNARK proof to guarantee aggregation integrity while preserving gradient privacy. Experiments demonstrate that zkFL exhibits strong robustness and verifiability in both IID and non-IID settings, outperforming prior methods, even in the presence of a malicious server.
With the rapid adoption of diffusion models for visual content generation, proving authorship and protecting copyright have become critical. This challenge is particularly important when model owners keep their models private and may be unwilling or unable to handle authorship issues, making third-party verification essential. A natural solution is to embed watermarks for later verification. However, existing methods require access to model weights and rely on computationally heavy procedures, rendering them impractical and non-scalable. To address these challenges, we propose NoisePrints, a lightweight watermarking scheme that utilizes the random seed used to initialize the diffusion process as a proof of authorship without modifying the generation process. Our key observation is that the initial noise derived from a seed is highly correlated with the generated visual content. By incorporating a hash function into the noise sampling process, we further ensure that recovering a valid seed from the content is infeasible. We also show that sampling an alternative seed that passes verification is infeasible, and demonstrate the robustness of our method under various manipulations. Finally, we show how to use cryptographic zero-knowledge proofs to prove ownership without revealing the seed. By keeping the seed secret, we increase the difficulty of watermark removal. In our experiments, we validate NoisePrints on multiple state-of-the-art diffusion models for images and videos, demonstrating efficient verification using only the seed and output, without requiring access to model weights.
The integration of blockchain technology into healthcare presents a paradigm shift for secure data management, enabling decentralized and tamper-proof storage and sharing of sensitive Electronic Health Records (EHRs). However, existing blockchain-based healthcare systems, while providing robust access control, commonly overlook the high latency in user-side re-computation of hashes for integrity verification of large multimedia data, impairing their practicality, especially in time-sensitive clinical scenarios. In this paper, we propose FAITH, an innovative scheme for \underline{F}ast \underline{A}uthenticated and \underline{I}nteroperable mul\underline{T}imedia \underline{H}ealthcare data storage and sharing over hybrid-storage blockchains. Rather than user-side hash re-computations, FAITH lets an off-chain storage provider generate verifiable proofs using recursive Zero-Knowledge Proofs (ZKPs), while the user only needs to perform lightweight verification. For flexible access authorization, we leverage Proxy Re-Encryption (PRE) and enable the provider to conduct ciphertext re-encryption, in which the re-encryption correctness can be verified via ZKPs against the malicious provider. All metadata and proofs are recorded on-chain for public verification. We provide a comprehensive analysis of FAITH's security regarding data privacy and integrity. We implemented a prototype of FAITH, and extensive experiments demonstrated its practicality for time-critical healthcare applications, dramatically reducing user-side verification latency by up to $98\%$, bringing it from $4$ s down to around $70$ ms for a $5$ GB encrypted file.
Venkata Sivakumar Musam, Nagendra Kumar Musham, C Siva, S. Karimulla Basha · 6 authors
The field of healthcare monitoring has been revolutionized by a combination of cloud computing and IoT-enabled sensor networks that enable real-time data collection, storage and processing. However, because healthcare data is sensitive, strong security and privacy-preserving measures are required to stop unwanted access and preserve data integrity in multi-authority settings. To propose a collaborative and privacy-preserving sensor cloud architecture for safe, scalable, and fine-grained access control for healthcare monitoring systems by utilizing Zero-Knowledge Proofs (ZKP) and Multi-Authority Attribute-Based Encryption (MA-ABE). The proposed method combines ZKP for authentication and MA-ABE for attribute-based encryption to protect sensitive data. It uses gateways to securely aggregate and transmit data to the cloud, and elliptic curve cryptography to optimize performance. The framework decreased computational overhead by 40% while achieving notable gains in encryption (120 ms) and decryption (150 ms). Outperforming current approaches in healthcare data security and access management, classification accuracy reached 96.5% with improved privacy preservation (96%) and scalability (94%). The suggested system addresses privacy, scalability, and computational efficiency while incorporating cutting-edge cryptographic approaches to provide secure healthcare monitoring. Large-scale, real-time healthcare applications can benefit greatly from its strong solution.
Octara Pribadi, Johanes Terang Kita Perangin Angin, Erick Erick
The development of information technology has driven the need for stronger security systems and guaranteed privacy on web-based platforms. Traditional verification methods such as passwords and two-factor authentication are increasingly seen as insufficient in facing the growing complexity of cyber threats. Zero-Knowledge Proof (ZKP) emerges as an alternative solution that enables identity verification without revealing sensitive information. This research aims to implement ZKP technology in web-based systems to enhance user security and privacy. The method involves the implementation of a simple XOR-based ZKP algorithm to prove identity without disclosing personal data, as well as a three-step verification mechanism between the verifier and the prover. Implementation results show that the system can prevent attacks such as man-in-the-middle and replay attacks, while maintaining data confidentiality during the authentication process. This study also identifies challenges in system efficiency and verification process integrity and offers technical solutions to support broader ZKP integration in digital platforms. Thus, the use of ZKP in web-based systems holds great potential to improve user trust and security in the digital era.
The rise of Central Bank Digital Currencies (CBDCs) or digital forms of central bank money represents a transformative shift in the global financial landscape, aiming to enhance financial inclusion, reduce transaction costs, and improve payment efficiency. While blockchain technology has been proposed as a foundational infrastructure for CBDCs, its suitability remains debatable. This paper provides a Systematization of Knowledge (SoK) on the application of blockchain in CBDCs, analyzing their potential benefits and challenges. We examine key aspects, including scalability, security, privacy, interoperability, environmental sustainability, offline functionality, regulatory considerations, and architecture design. To ground our analysis in practice, we review several real-world CBDC initiatives, including China’s eCNY, the Bahamas’ Sand Dollar, Nigeria’s eNaira, the European Central Bank’s digital euro initiative, Sweden’s eKrona, BIS’s CBDC projects, and Thailand’s CBDC journey. Finally, we highlight research challenges and future directions, including post-quantum cryptography for enhanced security, zero-knowledge proofs for preserving privacy, and AI-driven compliance automation. This study offers a comprehensive knowledge base for policymakers, researchers, and financial institutions to explore the blockchain-based CBDCs.
Lingyan Xue, Haiping Huang, Fu Xiao, Qi Li · 5 authors
Redactable blockchains are challenging the core principle of traditional blockchains: immutability. One such example is the chameleon hash-based blockchain. Despite rapid academic advances, most solutions have not yet simultaneously considered four key aspects: the degree of modification privileges, the transparency of the modification process, the consistency in the post-redaction global state, and system security after redaction. In this paper, we present a controllable, publicly auditable, and redactable blockchain with a main-auxiliary architecture. Specifically, we integrate weighted secret sharing, digital signature, and non-interactive zero-knowledge proof technologies to propose a verifiable and controllable chameleon hash primitive. To encourage logical nodes, it includes a reputation evaluation mechanism and a DAO-based governance model. Additionally, we construct a redactable bi-directionally anchored main-auxiliary blockchain structure, where the auxiliary chain exclusively maintains the modification proofs associated with each block of main chain. Any node can audit the modification history or, in the event of an accusation, self-prove. This structure also simplifies global state updates for newly joined or restarted nodes. Finally, we provide comprehensive security proofs for our construction, conduct extensive experiments to evaluate its functionality and performance, and compare it with analogous solutions to demonstrate its superiority.
Petitions are popular among internet users to share their opinions on various topics. However, most petitions are created and signed on few central platforms that retain control over content, participation and the technical implementation.Public Blockchains have the potential to increase trust in petition results, as their workings are transparent and the integrity of processed data is verifiable by anyone. We define the scope of petitions and their relationship to voting systems and present several approaches, ranging from Ethereum addressbased authentication and zero-knowledge proofs to pseudonymous signatures.These approaches are compared in terms of functional and security properties, cost and user requirements. Using the proposed methods, users can sign petitions based on their identity such that they are both universally verifiable and unique, without allowing attackers to infer their identities. We evaluate all schemes by deploying them to Ethereum-based blockchains and find that some of them fulfill all stated requirements and are practically usable on Layer 2 networks.
Built environments face significant challenges in promoting material reuse due to the lack of trustworthy and transparent trading mechanisms. Existing digital platforms often fail to ensure fairness, bid confidentiality, and auditability. To address this gap, this paper presents the design and implementation of a verifiable auction system for trading reusable construction materials. Built on a Polkadot-based platform, the system supports sealed reverse auctions through a hybrid on-chain/off-chain architecture: encrypted and signed bids are stored in InterPlanetary File System (IPFS), while a Merkle root of valid bids is committed on-chain. Zero-knowledge proofs (ZKPs) enable verification of bid correctness without revealing bid values. Stress testing showed moderate latency from proof generation and IPFS operations, yet performance remained suitable for auctions lasting minutes or hours. The results demonstrate a scalable, privacy-preserving, and auditable auction mechanism that leverages decentralised technologies to advance circular economy goals.