Digital transactions currently exceed trillions of dollars annually, yet traditional paper-based agreements remain a bottleneck for automation, enforceability, and dispute resolution. Natural language contracts introduce ambiguity, require manual processing, and lack computational verifiability, all of which hinder efficient digital commerce. Computable legal contracts, expressed in machine-readable formats, offer a potential solution by enabling automated execution and verification. Blockchain-based smart contracts further strengthen enforceability and accelerate dispute resolution; however, current implementations risk exposing sensitive agreement terms on public ledgers, raising serious privacy and competitive intelligence concerns that limit enterprise adoption. We introduce zk-agreements, a protocol designed to transition from paper-based trust to cryptographic trust while preserving confidentiality. Our design combines zero-knowledge proofs to protect private agreement terms, secure two-party computation to enable private compliance evaluation, and smart contracts to guarantee automated enforcement. Together, these components achieve both privacy preservation and computational enforceability, resolving the fundamental tension between transparency and confidentiality in blockchain-based agreements.
Decentralized Autonomous Organization operates without a central entity, being owned and governed collectively by its members. In this organization, decisions are carried out automatically through smart contracts for routine tasks, while members vote for unforeseen issues. Scalability in decisionmaking through voting on proposals is essential to accommodate a growing number of members without sacrificing security. This paper addresses this challenge by introducing a scalable and secure DAO voting system that ensures security through Groth16 zk-SNARKs and exponential ElGamal encryption algorithm while achieving scalability by verifiably delegating heavy computations to untrusted entities. While offline computation on the exponential ElGamal homomorphic encryption algorithm is enabled to reduce the computational cost of the blockchain, Groth16 is allowed to maintain robust off-chain calculation without revealing any further details. Specifically, the Groth16 proof guarantees that (i) the encrypted votes accurately reflect the voter's voting power, ensuring no unauthorized weight manipulation; (ii) only valid non-negative vote values are encrypted, preventing unintended or malicious vote tampering; and (iii) the homomorphic summation is performed correctly. The implementation shows that the proofs are verified remarkably fast, making the S2DV protocol highly suitable for scalable DAO voting, while preserving the security of the election.
This paper addresses the challenge of designing secure and private digital credentialing systems by leveraging advanced mathematical primitives from applied cryptography. The core of our proposed solution is the application of Zero-Knowledge Proofs (ZKPs), a class of cryptographic protocols that allows for the verification of assertions without disclosing the underlying secret data. We introduce a formal, layered architecture that demonstrates how the mathematical properties of ZKPs can be systematically translated into a robust, large-scale information system. The framework's design is validated against the complex requirements of the academic domain, which serves as a rigorous testbed for our architectural approach. The primary contribution is a blueprint for integrating complex cryptographic protocols into practical system design, demonstrating how mathematical guarantees of privacy can be preserved in a distributed and verifiable manner. This work provides a novel contribution at the intersection of applied cryptography, system architecture, and information security.
Abstract The increasing fragmentation of blockchain networks, compounded by recurring vulnerabilities in conventional cross-chain bridges—including censorship, replay attacks, and validator collusion—underscores an urgent need for secure and privacy-preserving interoperability protocols. This paper introduces ZK-InterChain, a protocol designed for unidirectional data transfers from consortium to public blockchains. The system empowers users to prove private or semi-private actions, such as verified purchases, without revealing their identities on the public network. The core of ZK-InterChain's architecture features a dual Zero-Knowledge Proof (ZKP) system. A client-side module facilitates user-generated proofs of private activity, while a validator-side module attests to state updates from the consortium chain using aggregated BLS signatures. Privacy is maintained through cryptographic nullifiers and minimal public inputs, which decouple a user's identity from their public-chain activities. Security analysis confirms the protocol's resilience against key attack vectors. Empirical evaluation demonstrates user-side proof generation in approximately one minute and validator-side state attestation in two minutes, with on-chain verification consuming approximately 220k gas. These performance characteristics establish ZK-InterChain as a viable solution for non-immediate, privacy-sensitive applications, such as decentralized reputation systems, post-event credentialing, and anonymous feedback mechanisms.
Saud Sultan Al Qasimi, Qassim Nasir, Manar Abu Talib
Secure, trustworthy electronic elections require four key properties: verifiable eligibility, strong ballot privacy, revoting for coercion resistance, and nation-scale throughput. Existing blockchain-based prototypes address these goals only in fragments, while verified credential to Zero Knowledge Proof (ZKP) conversion is ad hoc, re-voting schemes leak timing data or exhaust gas limits, and “track-your-vote” features issue receipts that a coercer can demand. ZKP-E-Vote closes these gaps with a fully specified architecture. A compulsory UAE-Pass login feeds a Groth16 circuit that converts government credentials into a non-linkable pseudonym$P$and a zero-knowledge eligibility proof. Ballots embed a monotone counter and a hash-derived nullifier, enabling any voter to overwrite a coerced ballot while revealing nothing regarding their re-vote. After polls close, threshold-decryption verification rooms let citizens confirm their own ballots without exporting a receipt; while a public zk-proof concurrently attests that every tallied ciphertext is the latest for its pseudonym and that the homomorphic total matches the announced result. All proofs are generated off-chain and recursively aggregated; relay nodes batch thousands of ballots into roll-up blocks, fixing onchain state at one 32-byte slot per voter, and bounding verification to a single pairing check per batch. The framework thus unites eligibility privacy, coercion-safe revoting, receipt-free voter assurance, and national-scale feasibility in a single auditable design, offering a concrete roadmap toward a pilot-ready blockchain election system.
Iván Abellán Álvarez, Pol Hölzmer, Johannes Sedlmeir
Digital identity wallets promise significant advancements in digital identity management by offering users a high degree of convenience, security, and control over their data disclosure. However, there is also criticism regarding their privacy guarantees, especially when used in regulated use cases that require high levels of assurance on the correctness and binding of a legal identity. In this paper, we present a comprehensive privacy model and analysis of one of the most prominent digital wallets – the European Digital Identity Wallet (EUDIW) – as specified by the Architecture and Reference Framework (ARF) and the eIDAS 2.0 regulation. We employ a suite of qualitative privacy risk assessment methods to systematically map and evaluate information flows in three key use cases. Our analysis identifies multiple privacy risks – including linkability, identifiability, and excessive attribute data disclosure – and reveals that although the ARF is designed to comply with privacy-by-design principles, inherent design choices, such as the reliance on SD-JWT and mDOC data formats, as well as the concept of a Wallet Unit Attestation (WUA), retain risks to user privacy. Building on our findings, we then highlight how advanced Privacy-Enhancing Technologies (PETs), such as (general-purpose) Zero-Knowledge Proofs (ZKPs), can reduce or mitigate some of these risks.
Energy consumption in Federated Learning (FL) has emerged as a major challenge due to the growing deployment of intelligent edge devices and the increasing complexity of machine learning models. FL enables collaborative model training across decentralized data sources without transferring raw data, thereby reducing communication overhead and enhancing data privacy by design. These features make FL particularly suitable for applications in healthcare, finance, and industrial IoT, where data sensitivity and resource constraints are critical. This paper provides a comprehensive survey of energy-efficient techniques in FL, classifying them into four main categories: model compression (including pruning and quantization), communication optimization, client selection, and hardware-aware strategies. The paper presents a unified taxonomy and discusses the strengths, limitations, and trade-offs of each approach. A comparative evaluation framework is introduced to assess energy savings, model accuracy, communication cost, and deployment feasibility. By analyzing current trends and open challenges, this review offers valuable guidance for researchers and practitioners in the development of scalable, energy-aware, and privacy-preserving federated learning systems.
Recent advances in lattice-based cryptography have seen Chen et al. introduce a linkable ring signature scheme (LLRS) for cloud-assisted electronic medical record systems, claiming dual security properties of linkability and unforgeability (IEEE Trans. Inf. Forensics Secur., doi: 10.1109/TIFS.2024.3455772). Our cryptanalysis reveals critical security flaws in their construction: the scheme fails to satisfy either claimed property. Specifically, we demonstrate universal forgeability through adaptive message attacks and identify defective linkability verification that permits signature origin ambiguity. Following vulnerability demonstrations via concrete attack vectors, we trace these weaknesses to flawed parameter initialization and improper nonce handling in their zero-knowledge proof framework. We conclude with concrete mitigation strategies including strengthened commitment schemes and improved randomness management.
Abstract Blockchain wallet manages decentralized identities in Web3, which allows users to identify themselves in a verifiable yet anonymous manner by digital signatures. However, native wallet scheme has been proven vulnerable to Sybil attacks in practice, where adversaries can easily create large numbers of controlled wallets at a low cost to undermine Web3 applications. To this end, many solutions are proposed for mitigating Sybil attacks. Nevertheless, they typically rely on either costly specialized biometric hardware or behavior-based heuristics that can be easily bypassed. In this paper, we introduce EdenDID, the first trinity-bound identity management system that uniquely binds human user, wallet address, and physical device into a unified framework. EdenDID combines edge-based video recognition, on-chain transactional activity analysis, and device computational power verification to establish a decentralized Proof-of-Trustworthiness consensus. The system provides compliant users with a trusted, verifiable credential to prove their unique identity. We prototype low-cost Eden Devices and deploy them on a Layer-2 blockchain network. Our experiments demonstrate the low end-to-end latency and robust resistance performance to Sybil attacks. Moreover, we present a case study to show how EdenDID can mitigate virtual-hardware fraud in DePIN, in which EdenDID successfully binds the user, wallet, and device uniquely, thus preventing users from binding multiple wallets or devices.
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.
Maximal Extractable Value (MEV) refers to a class of attacks to decentralized applications where the adversary profits by manipulating the ordering, inclusion, or exclusion of transactions in a blockchain. Decentralized Finance (DeFi) protocols are a primary target of these attacks, as their logic depends critically on transaction sequencing. To date, MEV attacks have already extracted billions of dollars in value, underscoring their systemic impact on blockchain security. Verifying the absence of MEV attacks requires determining suitable upper bounds, i.e. proving that no adversarial strategy can extract more value (if any) than expected by protocol designers. This problem is notoriously difficult: the space of adversarial strategies is extremely vast, making empirical studies and pen-and-paper reasoning insufficiently rigorous. In this paper, we present the first mechanized formalization of MEV in the Lean theorem prover. We introduce a methodology to construct machine-checked proofs of MEV bounds, providing correctness guarantees beyond what is possible with existing techniques. To demonstrate the generality of our approach, we model and analyse the MEV of two paradigmatic DeFi protocols. Notably, we develop the first machine-checked proof of the optimality of sandwich attacks in Automated Market Makers, a fundamental DeFi primitive.
R. Raja Sekar, Bhavesh Shankar Kalluru, Imran Sunkesula, Gopi Krishna Chimata · 5 authors
Blockchain mechanism, having its distributed and immutable nature, has become a revolutionary method of secure and transparent data exchange. With this potential in mind, our proposal is for Secure File Sharing System that combines AES-256&DES encryption with Ethereum smart contracts to provide a privacy-oriented and audit-ready file sharing system. The conventional centralized approach is prone to data leakages and unauthenticated access, but with the use of blockchain and encryption, this approach provides confidentiality along with trustless verification. Files are first encrypted at the server level using AES, DES symmetric encryption, thus avoiding any plaintext exposure at the server level. The file is stored encrypted within a cloud storage service called cloudinary, with sensitive metadata such as hashed file ID, destination wallet address, and unlock timestamp stored on the Ethereum blockchain through smart contracts. The blockchain layer delivers traceability and immutability with accessed file records being tamperproof. In addition, there is a time-lock mechanism in the smart contract that doesn't allow recipients to access files before the unlock time, thereby improving security and governance. The React.js frontend communicates with blockchain networks using MetaMask and ethers.js, while the Node.js and Express backend encrypts and decrypts the files, and stores metadata in MongoDB. This two-way hybrid approach effectively addresses attacks such as unauthorized access, man-in-the-middle, and data tampering. With this blend of blockchain's decentralized trust and AES's and DES's secrecy, this project lays out an innovative and viable model for secure file sharing digitally. It is robust in possible application to actual applications like enterprise document management, transfer of legal documents, and confidential communication, and provides a secure, transparent, and scalable solution.
This article explores the characteristics of data resources from the perspective of production factors, analyzes the demand for trustworthy circulation technology, designs a fusion architecture and related solutions, including multi-party data intersection calculation, distributed machine learning, etc. It also compares performance differences, conducts formal verification, points out the value and limitations of architecture innovation, and looks forward to future opportunities.
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.
Jeffson C. Sousa, Bruno Evaristo, Vinicius Duarte, Mauricio Pinto · 6 authors
Blockchain technology has established itself as a decentralized solution capable of ensuring security, transparency, and robust process validation, profoundly transforming various sectors. This work proposes the development of an innovative marketplace for the telecommunications sector, based on blockchain, with the aim of providing a dynamic catalog of telecom services and assets. The platform enables asset and service providers to publish offers for physical resources-such as towers, antennas, and links-within an integrated market. These resources can be hired by third parties under Business-to-Business (B2B) and Business-to-Consumer (B2C) models. The architecture incorporates decentralized identity (DID), smart contracts for asset tokenization and automated billing, and a lightweight frontend. Built on Hyperledger Besu and integrated with Ethereum-compatible libraries, the system fosters digital governance, interoperability, and the sustainable use of underutilized physical assets.
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.
Smart contracts are commonly used for automated processing on blockchains, and research related to smart contracts is actively conducted. However, smart contracts are constrained by the fact that they cannot hold secret information due to transparency requirements, and thus smart contracts cannot perform calculations using secret information. In particular, they generally cannot generate digital signatures, which are computations using a secret key. This limits the potential of smart contracts. In this study, we propose a new scheme that enables smart contracts to generate signatures even if the smart contract does not hold a secret key. The proposed scheme allows smart contracts to securely delegate signature generation to off-chain servers that hold the signing key and do not support TEE. Even if the off-chain server is compromised by an attacker and the secret key (signing key) is stolen, the smart contract still generates a valid signature. We provide a new secure and effective signature generation approach using smart contracts and incentive mechanisms, even if the signing key is publicly available.
A polynomial commitment scheme (PCS) enables a prover to commit to a polynomial and later prove the correctness of its evaluation without revealing the polynomial. Although discrete logarithm-based PCSs offer succinct proofs, they are not quantum-safe. Lattice-based PCSs provide post-quantum security and additive homomorphism, making them suitable for applications such as zero-knowledge proofs and secure multiparty computation. In this article, we review two recent lattice-based PCSs, Greyhound and HyperWolf, both relying on the Module-SIS assumption but differing in target polynomial classes and proof techniques. In particular, Greyhound achieves a smaller proof size O(log log N) through folding and LaBRADOR proofs, while HyperWolf supports univariate and multilinear polynomials with lower verifier cost O(log N) using hypercube evaluation.