With the widespread adoption of Internet of Things (IoT) technologies in healthcare systems, security issues related to user privacy during data transmission and sharing have become increasingly prominent. To address these challenges, this paper proposes a medical privacy protection and secure sharing scheme based on Quantum Key Distribution (QKD). The scheme integrates multiple technologies, including blockchain, smart contracts, zero-knowledge proofs, and Chebyshev chaotic mapping, to ensure secure data sharing and access control among multiple communication entities. Compared with existing solutions, our approach enhances key management security through quantum keys and improves communication resilience against attacks by leveraging chaotic systems. User identity privacy is protected via zero-knowledge proofs. Under the random oracle model, the security of the proposed scheme is formally proven. Moreover, comparative experiments with existing protocols demonstrate the scheme's comprehensive advantages in terms of security and performance, evaluated across throughput, computational overhead, communication overhead, and storage overhead.
Existing electronic voting systems suffer from security concerns, identity theft, electoral fraud, and insufficient transparency in digital voting systems, which pose significant challenges to electoral integrity. Blockchain-based electronic voting systems provide immutability and decentralization. However, they are inappropriate for large-scale elections because of their inadequate consensus mechanisms, scalability issues, and security weaknesses. To provide an equitable electoral process, an electronic voting system must be scalable, secure, and efficient. This method requires real-time vote verification, secure vote recording to avert fraud, and voter authentication. This study introduces a blockchain-based smart contract electronic voting system (BCVS) to improve the security and efficiency of electronic voting. The three algorithms are employed by the proposed BCVS to safeguard and improve the electronic voting process via the utilization of smart contracts. These algorithms ensure the precise tabulation of results and establish a robust foundation for electronic voting by resolving disputes. The proposed approach ensures transparency, immutability, and a minimal likelihood of manipulation through the utilization of the prioritized delegated proof-of-stake (PDPoS) consensus mechanism. The PDPoS functions on Tier 3 scalable networks and diligently documents transactions on the blockchain to resolve critical challenges associated with electronic voting. The scalability and integrity of the proposed e-voting system are ensured through the implementation of a practical Byzantine fault tolerance algorithm. Improved voter authentication is accomplished by multi-factor authentication and elliptic curve digital signatures, reducing the dangers of unwanted access. Additionally, Nightshade sharding from the NEAR algorithm enhances scalability by partitioning the blockchain network into numerous smaller shards, facilitating parallel transaction processing. Consequently, throughput is markedly enhanced, and latency is diminished. The testing results indicate that the proposed BCVS achieves 100% confirmed transactions, 98% compatibility, 95% accuracy, and 95% audited votes. The proposed BCVS outperforms existing state-of-the-art systems in multiple essential domains, such as the volume of votes cast within a specified timeframe, precision, interoperability with other systems, quantity of confirmed transactions, auditability, and duration of vote counting.
This study introduces a framework that integrates blockchain, decentralized identity, and zero-knowledge proofs to enhance the trustworthiness and confidentiality of disaster information sharing. A sustainable model is proposed for real-world applications, supported by a prototype developed on the Decentralized Solutions for Humanity (DS4H) blockchain research network.
Emanuela Podda, Pol Hölzmer, Alexandre Amard, Johannes Sedlmeir · 5 authors
Zero-knowledge proofs allow the implementation of the data minimisation principle imposed by the GDPR in digital identity wallets and the related personal data transactions, therefore representing a reasonable option to be enforced by lawmakers.
Efficient cryptographic verification methods are critical for secure communication in intelligent transportation systems (ITS), especially with the proliferation of Internet of Vehicles (IoV) devices powered by consumer technology. However, traditional zero-knowledge proofs often face efficiency limitations. This paper proposes a novel verifiable decryption scheme for IoV applications within ITS, leveraging the Module Learning with Errors (MLWE) and Module Small Integer Solution (MSIS) problems to address these challenges using widely available consumer technology platforms. The scheme integrates a compression function tailored for IoV devices and consumer technology in intelligent transportation systems, coupled with error estimation techniques, effectively mitigating disparities in equality relationships between the private data of the prover and verifier during the encryption and decryption process. This enables the prover to selectively share partial information, reducing discrepancies and transforming the verifiable decryption problem into a proof that a vector in the ring satisfies a linear relationship. A rigorous theoretical analysis demonstrates the schemes correctness, security, communication overhead, and computational complexity, reducing its soundness and zero-knowledge properties to the hardness assumption of the MSIS problem. The paper also recommends two parameter sets for different security levels that are feasible for deployment on consumer technology devices. To evaluate the schemes practicality, a C-language implementation was developed and tested on typical consumer technology hardware. Experimental results show significant advantages in proof size and computation time for a single ciphertext compared to existing schemes, making the proposed method highly efficient for ITS scenarios. This verifiable decryption scheme offers a post-quantum cryptographic solution that ensures secure, efficient, and scalable data exchange, aligning with the stringent demands of intelligent transportation systems and leveraging the accessibility of consumer technology.
In our research, we propose the first practically deployable construction of a multi-prover zero-knowledge succinct non-interactive argument of knowledge (zkSNARK) protocol specifically tailored for restricted multiplication straight-line (RMS) programs, a computation model widely applicable in evaluating polynomials. Our protocol ensures input privacy, zero-knowledge, and security against fully malicious provers, all while eliminating the need for any inter-prover communication, making it highly suitable for distributed cloud environments. At the core of our approach is the introduction of the Restricted Quadratic Arithmetic Program model, an algebraic structure aligned with RMS semantics that enables provers to independently generate local proofs. We instantiate our framework using the Pinocchio protocol, resulting in a system that requires only 9 group elements per proof and 10 pairings for verification, nearly matching the efficiency of its single-prover counterpart. By leveraging our multi-prover zkSNARK protocol within a multi-server verification computation framework, we enable secure outsourcing of computations to the cloud of fully untrusted cloud servers. Compared to existing works, our protocol uniquely eliminates the need for any inter-server communication while achieving security even against adversaries controlling all servers.
Rudraksh Joshi, Amrit K. Goel, Prashant Singh, Jitendra Goyal
Blockchain is a distributed ledger technology designed to ensure transparent and tamper-proof transaction recording without centralized control. Despite its benefits, this transparency can compromise the confidentiality of the data. This paper investigates eight privacy-preserving methods such as encryption, steganography, off-chain hashing, and zero-knowledge proofs. Each technique is explored through working implementations and real-world constraints, including gas cost and legal compliance. A hybrid architecture is proposed that blends on-chain verification with IPFS-based off-chain storage, enabling developers to build scalable and privacy-conscious decentralized applications.
Blockchain has the potential to be a game changer in the way health records are managed; it's secure, transparent and decentralized. Legacy EHR systems are plagued with data breaches, and interoperability challenges, as well as a central point of failure. Blockchain addresses these risks through its public ledger, cryptographic encoding, and consensus-driven verification, which all contribute to making health records tamper-resistant and auditable. Smart contracts automate access control so that you can share patient data with other authorized parties securely and in line with HIPAA or GDPR. The decentralized nature of blockchain also eliminates single points of failure, which mitigates the risk of hacking and unauthorized access. Further, blockchain promotes interoperation through normalization in data formats, such as Fast Healthcare Interoperability Resources (FHIR), and facilitates the sharing of data between institutions while preserving privacy. Scalability solutions in the form of sharding and layer-2 protocols allow large-scale medical data to be processed in a decentralized manner while new consensus algorithms (e.g., Proof-of-Stake) keep energy consumption down. Much like transportation, there are some key challenges, such as regulatory adherence and compatibility with existing systems. Still, if used properly, blockchain could serve as a transparent, secure, and patient-centric model for health record management. New developments in post-quantum cryptography, AI-platform deeds and smart contracts will continue to reinforce blockchain's contribution to disrupting healthcare data management.
Zeyad Ghaleb Al-Mekhlaf, Murtaja Ali Saare, Jalal Mohammed Hachim Altmemi, Mahmood A. Al-Shareeda · 9 authors
The rapid adoption of Internet of Medical Things (IoMT) devices enables real-time patient monitoring and remote diagnostics and has revolutionized healthcare delivery. Traditional cryptographic schemes like RSA and ECC, which rely on meaningful mathematical challenges, are under great threat from quantum computing, threatening sensitive medical data confidentiality and integrity. This paper proposes a quantum-resistant healthcare security framework based on lattice-based cryptographic primitives such as Learning With Errors (LWE), Ring-LWE (RLWE), and Short Integer Solution (SIS). To this end, we design a five-phase IoMT-friendly framework—Initialization, Registration, Authentication, Data Exchange, and Treatment—where each phase is backed up by lightweight cryptography primitives that can be easily implemented on the low-resource IoMT devices. Relative to the state-of-the-art lattice- and hash-based constructions, our framework involves 50-75% smaller ciphertext sizes, up to a 50% reduction of the communication overhead, and nearly 60% less in computational cost. Furthermore, the solution relies on zero-knowledge proofs, homomorphic encryption as well and attribute-based access control to guarantee strong security and privacy. Using the AVISPA tool, the framework is formally verified, showing its resistance against classical and quantum adversaries. Focusing on tangible healthcare threats, including data tampering and unlicensed access to patient diagnostics, this research paves the way for scalable, efficient, and quantum-resistant medical data protection. Our results pave the way for future investigations into secure post-quantum healthcare and IoT applications.
Tao Wang, Keyong Hong, Bo Yang, Qiliang Yang · 6 authors
The rapid growth in the NFT (Non-fungible token) market has offered a wide variety of opportunities for scammers, fraudsters, wash tradings, and so on. One of the most urgent security issues is how to efficiently authorize and validate the ownership to make the NFT ecosystem avoid infringement and counterfeiting. By exploiting linear homomorphic tagging and robust digital watermarking technologies, this article proposes a generic framework for ownership authorization and batch validation of NFTs. Within this framework, the digital artwork creators can authorize the ownership to a buyer before the NFT is minted in the public blockchain. Anytime in the future who questions the ownership of a claimant can initiate a validation procedure to get an auditing report by running a Challenge-Response protocol that supports efficient batch verification. The completeness and soundness of the proposed framework have been proven by assuming a secure homomorphic tag scheme and a robust watermarking scheme. We also present instantiations of the generic construction, especially with$\Pi _{Pub}$, one can outsource the validation procedure to the public blockchain to release local computation burden. A series of elaborated experiments have shown our proposed framework is practical and efficient.
The rapid digitization of e-government systems has introduced significant privacy challenges, including unauthorized data access and identity theft, which threaten the integrity and trustworthiness of public services. This study proposes a privacy protection framework based on Zero-Knowledge Proofs (ZKP), a cryptographic technique enabling secure verification without revealing sensitive information. The framework addresses critical privacy concerns such as secure identity verification, data confidentiality, and compliance with regulatory standards. By integrating advanced ZKP schemes, including Succinct Non-Interactive Arguments of Knowledge (zk-SNARKs) and Bulletproofs, the framework ensures efficient proof generation and verification while minimizing computational overhead. A performance evaluation demonstrated that the proposed framework reduces privacy risks by 78% and achieves a threefold increase in transaction throughput compared to traditional cryptographic methods, such as Rivest–Shamir–Adleman (RSA) and Public Key Infrastructure (PKI). The scalability and efficiency of the framework were validated through extensive computational overhead analysis and comparative benchmarking. Additionally, trusted setup optimizations and constraint system modeling were employed to enhance the framework’s robustness and adaptability for large-scale e-government applications.
Zero-Knowledge Proofs (ZKPs) are critical for privacy-preserving techniques and verifiable computation. Many ZKP protocols rely on key kernels such as the SumCheck protocol and Merkle Tree commitments to enable their key security properties. These kernels exhibit balanced binary tree computational patterns, which enable efficient hardware acceleration. Although prior work has investigated accelerating these kernels as part of an overarching ZKP protocol, exploiting this common tree pattern remains relatively underexplored. We conduct a systematic evaluation of these tree-based workloads under different traversal strategies, analyzing performance on multi-threaded CPUs and the Multifunction Tree Unit (MTU) hardware accelerator. We introduce a hardware-friendly Hybrid Traversal for binary tree that improves parallelism and scalability while significantly reducing memory traffic on hardware. Our results show that MTU achieves up to $1478\times$ speedup over CPU at DDR-level bandwidth and that our hybrid traversal outperforms breadth-first search by up to $3\times$. These findings offer practical guidance for designing efficient hardware accelerators for ZKP workloads with binary tree structures.
Lambard Maxence, Cyrille Bertelle, D apos Amours Claude
In an increasingly complex contractual landscape, the demand for transparency, security, and efficiency has intensified. Blockchain technology, with its decentralized and immutable nature, addresses these challenges by reducing intermediary costs, minimizing fraud risks, and enhancing system compatibility. Smart contracts, initially conceptualized by Nick Szabo and later implemented on the Ethereum blockchain, automate and secure contractual clauses, offering a robust solution for various industries. However, their complexity and the requirement for advanced programming skills present significant barriers to widespread adoption. This study introduces a multi-level finite state machine model designed to represent and track the execution of smart contracts. Our model aims to simplify smart contract development by providing a formalized framework that abstracts underlying technical complexities, making it accessible to professionals without deep technical expertise. The hierarchical structure of the multi-level finite state machine enhances contract modularity and traceability, facilitating detailed representation and evaluation of functional properties. The paper explores the potential of this multi-level approach, reviewing existing methodologies and tools, and detailing the smart contract generation process with an emphasis on reusable components and modularity. We also conduct a security analysis to evaluate potential vulnerabilities in our model, ensuring the robustness and reliability of the generated smart contracts.
Reisha Ali, Akshat Gupta, Maria Francis, Kotaro Kataoka
Decentralized applications (DApps) over blockchains often require the user’s personal information for authentication. However, the public and transparent nature of blockchains can compromise user privacy. Threshold-based anonymous credentials (TAC) provide anonymous and unlinkable authentication, which helps preserve user privacy. Additionally, the design of TAC aligns well with blockchain’s decentralized nature because TAC offers decentralized trust distribution to prevent a single point of failure. However, only a few of them have implementations over blockchains because TAC requires computationally expensive cryptographic operations such as pairings and verification of zero-knowledge proofs (ZKPs) to be done on-chain. Thus, existing TAC systems have not been evaluated in a public permission-less blockchain environment. This evaluation is crucial to assess the efficiency and practicality of deploying TAC in real-world blockchain use cases to make TAC based DApps development feasible. This work presents the design and evaluation of three state-of-the-art TAC systems, RP-Coconut, threshold BBS+ (T-BBS+), and BBS (T-BBS), over the Ethereum blockchain. The evaluation compares the performance of these TAC systems on the Sepolia testnet in terms of execution time and gas usage. Additionally, this work also proposes partial credential verification mechanisms for T-BBS+ and T-BBS that significantly reduce the complexity of identifying valid credentials, thereby lowering the execution time at the user’s end. Furthermore, the implementation for blind issuance and associated ZKPs for T-BBS is provided, which was not previously detailed in the literature and is critical for its correct implementation.
Blockchain technology offers a decentralized ledger where all transactions are transparently recorded. While this transparency facilitates trustless verification, it also raises critical privacy concerns: large-scale data collection and analytics can link and trace user addresses, undermining the pseudonymity once considered sufficient. In this paper, we propose ZK-R-SNARK, a novel scheme that integrates Zero-Knowledge Proofs (ZK-SNARKs) with Ring Signatures to enhance transactional anonymity in public blockchain networks. Our approach utilizes ring signatures to ensure that the originating signer remains indistinguishable among a group of potential signers, while ZK-SNARK ensures succinct and non-interactive verification of the signature’s correctness. By combining these techniques, ZK-R-SNARK enables nodes to validate the authenticity of transactions without revealing any critical information about the sender’s identity or transaction details. As a result, even advanced data analytics or machine learning techniques have limited capability to cluster or link addresses over time. We implement our scheme in the Circom framework to demonstrate its feasibility and measure performance metrics such as proof generation time, verification overhead, and on-chain data size. Experimental results indicate that ZK-R-SNARK achieves robust privacy guarantees with acceptable computational costs for practical blockchain environments.
After successfully transitioning from proof-of-work to proof-of-stake, the Ethereum blockchain’s developer community has set an ambitious goal of achieving rapid block finalization, ideally completing it before the next block proposal, a concept known as single slot finality. Currently, block finalization on the ETH beacon chain takes ∼ 15 minutes to collect the attestation from the majority of the validators. The current protocol has several drawbacks, including slow finalization, high bandwidth usage and a rigid aggregation structure that is prone to failures. The challenge is collecting cryptographic signatures from close to a million validators distributed worldwide, connected to the network in 12 seconds without requiring high bandwidth internet connections from the peers in the network. This study presents an alternative scheme that has the potential to realize single-slot finality. Ours is a fully decentralized approach in which no node has a specific role, rendering it more robust than the current one. We simulate our heuristics on the Ethereum network topology and demonstrate that it can efficiently collect a million attestations from almost ten thousand physical nodes.
As the demand for e-voting grows, it has become particularly important to ensure the security and fairness of the voting system. Therefore, an e-voting system is studied and designed to ensure the non-tamperability of voting results. The system utilizes zero-knowledge proof to verify the identity of the voter, while ensuring the tamperability of the voting data through blockchain technology. The experimental results indicated that the system outperformed the existing schemes in terms of processing speed and verification efficiency. Specifically, when the number of voters was 200, the time consuming and single verification time of this system were 3.7 s and 6.4 ms, respectively. When the number of voters increased to 600, the time consuming and single verification time were 8.3 s and 13.3 ms, respectively. In the number of candidates/voters was 5/80, none of the system’s gas consumption exceeded the maximum limit of a single transaction in Ether. Among them, the gas consumption of Vote Control contract was 5577485, and the gas consumption of non-interactive zero knowledge contract was 3826753. Furthermore, the more candidates there were, the longer it took the system to operate, although the number of voters had less of an effect on the cost of operating the voter system. The above outcomes reveal that the e-voting system proposed in the study provides a secure and efficient solution for small-scale voting activities and provides a basis for future optimization of large-scale voting scenarios.
The increasing adoption of Decentralized Applications (DApps) and Web3 infrastructures has exposed critical security challenges, including malicious smart contracts, fraudulent transactions, and decentralized governance exploits. Traditional threat intelligence systems rely on centralized security models, which create single points of failure, reduce data sovereignty, and limit real-time risk mitigation. To address these challenges, we introduce a Decentralized Federated Risk Analysis (DFRA) system, leveraging federated risk aggregation, decentralized storage, and automated security intelligence retrieval to enhance cybersecurity in DApps. Our DFRA system operates through three primary components: (1) Federated Risk Aggregation, where a federated model retrieves and consolidates risk scores, flagged threats, and security insights across decentralized sources; (2) MinIOBased Decentralized Storage, which stores security intelligence in an object storage system to allow distributed retrieval; and (3) Automated Security Intelligence Retrieval, a server-based process that periodically fetches and processes security data in real-time.
E-voting has undergone significant advancements in recent years, nevertheless, ensuring the privacy, confidentiality, and integrity of voters' identities and their votes remains a crucial challenge. Blockchain technology, with its decentralized architecture and immutability, provides a promising solution for developing secure and transparent E-voting systems. Blockchain improves integrity and non-repudiation, however, its transparency compromises voters' anonymity, and the secrecy of vote contents. We propose in this paper an E-voting system that incorporates secure and privacy-preserving mechanisms based on a combination of Blockchain, and lightweight cryptographic techniques to address these issues, while mitigating the weaknesses of the most recent works such as Thakkar et al.'s voting system in which votes remain unencrypted. Moreover, the integration of advanced cryptographic techniques, as explored in Wang et al.'s work, inevitably introduces significant computational costs. The proposed system enables the verification of voter eligibility and the correctness of votes without revealing sensitive information while reducing computational costs. In our experimentation, we adopt smart contracts to implement the proposed system using solidity programming language, and deployed on Ethereum Blockchain. We evaluated our proposed system in terms of execution time and gas consumption. The obtained results proved its effectiveness compared to the most recent works.
Xin Liu, Xinyuan Guo, Dan Luo, Liang Li · 9 authors
Federated learning promotes the development of cross-domain intelligent applications under the premise of protecting data privacy, but there are still problems of sensitive parameter information leakage of multi-party data temporal alignment and resource scheduling process, and traditional symmetric encryption schemes suffer from low efficiency and poor security. To this end, in this paper, based on the modified NTRU-type multi-key fully homomorphic encryption scheme, an asymmetric algorithm, a secure computation scheme of multi-party least common multiple and greatest common divisor without full set under the semi-honest model is proposed. Participants strictly follow the established process. Nevertheless, considering that malicious participants may engage in poisoning attacks such as tampering with or uploading incorrect data to disrupt the protocol process and cause incorrect results, a scheme against malicious spoofing is further proposed, which resists malicious spoofing behaviors and not all malicious attacks, to verify the correctness of input parameters or data through hash functions and zero-knowledge proof, ensuring it can run safely and stably. Experimental results show that our semi-honest model scheme improves the efficiency by 39.5% and 45.6% compared to similar schemes under different parameter conditions, and it is able to efficiently process small and medium-sized data in real time under high bandwidth; although there is an average time increase of 1.39 s, the anti-malicious spoofing scheme takes into account both security and efficiency, achieving the design expectations.
Yao Ma, Wen Yu Kon, J. O. Chu, Kevin Han Yong Loh · 6 authors
Identity verification is the process of confirming an individual's claimed identity, which is essential in sectors like finance, healthcare, and online services to ensure security and prevent fraud. However, current password/PIN-based identity solutions are susceptible to phishing or skimming attacks, where malicious intermediaries attempt to steal credentials using fake identification portals. Alikhani et al. [Nature, 2021] began exploring identity verification through graph coloring-based relativistic zero-knowledge proofs (RZKPs), a key cryptographic primitive that enables a prover to demonstrate knowledge of secret credentials to a verifier without disclosing any information about the secret. Our work advances this field and addresses unresolved issues: From an engineering perspective, we relax further the relativistic constraints from 60m to 30m, and significantly enhance the stability and scalability of the experimental demonstration of the 2-prover graph coloring-based RZKP protocol for near-term use cases. At the same time, for long-term security against entangled malicious provers, we propose a modified protocol with comparable computation and communication costs, we establish an upper bound on the soundness parameter for this modified protocol. On the other hand, we extend the two-prover, two-verifier setup to a three-prover configuration, demonstrating the security of such relativistic protocols against entangled malicious provers.