With the rapid advancement of the digital age, the Internet has become an integral part of daily life. While users benefit from the convenience of online services, they are increasingly confronted with a critical conflict between identity privacy and security. Under traditional authentication mechanisms, malicious actors often exploit the login channel immediately after user registration, leading to the leakage of personal data. To address this issue, this paper proposes an anonymous identity authentication scheme based on non-interactive zero-knowledge proof. By employing ring signatures in combination with non-interactive zero-knowledge proofs, the proposed method ensures both the legitimacy of user identities and the security of the authentication process. Furthermore, the use of national cryptographic algorithms enhances the scheme's resilience against external attacks. Finally, we conduct comparative experiments to evaluate the proposed scheme. The results demonstrate that it provides anonymity, zero-knowledge soundness, resistance to quantum attacks, replay attacks, and double-spending. Additionally, the scheme achieves higher efficiency in signature generation and verification compared to an RSA+SHA-based ring signature authentication approach.
This article examines the evolving landscape of blockchain technology as a security framework across diverse domains. Blockchain's fundamental architecture—based on decentralization, immutability, transparency, and cryptographic security—offers distinctive advantages in addressing contemporary cybersecurity challenges. The article explores established implementations and cutting-edge innovations in blockchain security, including decentralized identity management, supply chain integrity verification, quantum-resistant cryptography, cross-chain interoperability protocols, and integration with artificial intelligence. Zero-knowledge proofs and other privacy-enhancing techniques are evaluated for their contribution to confidential yet verifiable transactions. Throughout these applications, blockchain demonstrates its capacity to create resilient systems that establish trust without centralized authorities, maintain data integrity in adversarial environments, and adapt to emerging threats. By shifting security paradigms from centralized to distributed models, blockchain technology presents transformative solutions to persistent vulnerabilities in digital infrastructure.
The inevitable advance of quantum computing presents significant challenges to current API security frameworks that predominantly rely on classical cryptographic algorithms. This article examines how emerging post-quantum cryptographic technologies are reshaping API security landscapes in preparation for a quantum-capable future. From lattice-based algorithms like CRYSTALS-Kyber and Dilithium to Quantum Key Distribution networks achieving secure communications across intercontinental distances, a new generation of security mechanisms is being developed to safeguard API infrastructures against quantum threats. Beyond defensive applications, quantum computing offers transformative capabilities for API operations, including enhanced traffic prediction through variational quantum circuits, intelligent resource allocation with unprecedented accuracy, and anomaly detection systems capable of identifying sophisticated attack patterns that evade conventional monitoring. The integration of quantum-resistant Zero-Knowledge Proofs is simultaneously enhancing authentication processes while minimizing credential exposure. Together, these innovations are creating a comprehensive framework for API security that not only protects against future quantum threats but delivers immediate benefits in performance, privacy, and operational efficiency for organizations dependent on API communications.
Shanmuga Sundaram Palaniswamy, M Jayaprakash, S. Loganathan, E. D. T. · 6 authors
The Internet of Things, commonly known as IoT, has transformed many sectors by allowing devices to connect and communicate effortlessly. Despite these benefits, this connectivity also leads to major concerns regarding privacy and security, especially when it comes to sensitive information. This paper offers an in-depth review of privacy-centric protocols based on blockchain technology that aim to tackle these issues and protect the sharing of IoT data. The research investigates how different blockchain systems (such as public, private, and consortium types), along with smart contracts, zero-knowledge proofs, and various encryption strategies, can be applied. By analysing numerous case studies and real-life instances, the review assesses how effectively these protocols maintain the confidentiality and integrity of data. It highlights important elements like transaction speed, scalability, and resource allocation. The results suggest that protocols utilizing blockchain provide enhanced data privacy and a lower risk of data breaches compared to conventional methods. For example, smart contracts streamline business transactions, while encryption safeguards data both during transmission and when stored. Nonetheless, issues regarding scalability, integration, and user acceptance still exist. This review offers critical insights for researchers, industry experts, and policymakers focused on enhancing the security of IoT solutions with the help of blockchain technology. This paper evaluates blockchain-based privacy-preserving protocols that facilitate secure IoT data exchange, concentrating on how well they maintain data confidentiality and integrity. By using case studies and practical assessments, the research identifies Hyperledger Fabric as the most effective protocol for IoT applications with high demands. The paper also addresses difficulties concerning scalability, performance, and integration, offering suggestions for future investigation.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Abstract: In modern democracies, secure and transparent voting mechanisms are critical for ensuring public trust and electoral integrity. Traditional voting systems often face challenges such as tampering, identity fraud, and lack of transparency. This paper proposes a Blockchain-Based Voting System designed to address these issues by integrating advanced technologies including Zero-Knowledge Proofs (ZKP), InterPlanetary File System (IPFS), and the Polygon Proof-of-Stake (PoS) blockchain. The system incorporates Aadhaar-based identity verification with OTP authentication to ensure that only eligible citizens can vote, while preserving voter anonymity through the implementation of ZKP. All sensitive data, including votes and candidate information, are recorded on the decentralized Polygon network, ensuring immutability and transparency. IPFS is employed for storing large files such as candidate profiles and voting records in a secure and distributed manner. Smart contracts automate the core election functions such as vote casting, validation, and result declaration, thereby minimizing the risk of human error and manipulation. A modular user interface is provided for both voters and election administrators, facilitating real-time monitoring, seamless authentication, and secure participation. By leveraging blockchain’s trustless architecture and privacypreserving cryptographic protocols, the proposed system aims to modernize the electoral process, enhance voter confidence, and strengthen democratic institutions in the digital age.The architecture ensures end-to-end verifiability, making each vote independently auditable without compromising confidentiality. This integration of privacy, security, and scalability offers a robust foundation for next-generation electoral systems.
S. Aarthi, K. Aravinthan, R. N. Ravikumar, N. Sivakumar · 5 authors
Data protection relies on cryptography to secure data across Blockchain, IoE, and Federated Learning systems. Strong cryptographic methods ensure confidentiality, authenticity, and integrity, safeguarding evolving digital security needs. Key techniques include symmetric and asymmetric encryption, hash functions, digital signatures, and zero-knowledge proofs. Cryptography enables secure protocols like TLS, homomorphic encryption, and differential privacy while addressing quantum-resistant security challenges, ensuring robust digital privacy solutions.
Yalan Wang, Liqun Chen, Yangguang Tian, Long Meng · 5 authors
Abstract The World Wide Web Consortium (W3C) has established standards for decentralized identities (DIDs) and verifiable credentials (VCs). A DID serves as a unique identifier for an entity, while a VC validates specific attributes associated with the DID holder. To prove ownership of credentials, users generate verifiable presentations (VPs). To enhance privacy, the W3C standards advocate for randomizable signatures in VC creation and zero-knowledge proofs for VP generation. However, these standards face a significant limitation: they cannot effectively verify cross-domain credentials while maintaining anonymity. In this paper, we present Anonymous Verifiable Presentations with Extended Usability (AVPEU), a novel framework that addresses this limitation through the introduction of a notary system. At the technical core of AVPEU lies our proposed randomizable message-hiding signature scheme. We provide both a generic construction of AVPEU and specific implementations based on Boneh–Boyen–Shacham, Camenisch–Lysyanskaya, and Pointcheval–Sanders signature. Our experimental results demonstrate the feasibility of these schemes.
Team lead at Upland.me Poland, Warsaw, Poltavskyi Dmytro
This article examines the role cryptographic methods play in protecting digital assets through blockchain systems, with a particular focus on their adjustment to contemporary challenges and technological trends. An endeavor is undertaken to systematize major cryptographic algorithms, their effective appraisal in data protection, and development prospects under quantum computing threats. The study is relevant because centralized systems increasingly depend on cryptography due to greater regulatory pressures and, above all, a need for security through secrecy. The scientific novelty lies in the detailed comparative analysis of the said methodology (hashing, digital signatures, zero-knowledge proofs) for cases relating to major blockchain platforms (Bitcoin, Ethereum, Zcash), which hence demonstrate varied approaches towards security provision. The study's methodological foundation consists of analyzing 13 sources, merging a qualitative examination of algorithms and ECDSA with zk-SNARKs with a quantitative assessment of their effectiveness. Hash functions and Merkle trees ensure data integrity while reducing the computational costs of verification; asymmetric cryptography and Zero-Knowledge Proofs guarantee authenticity and confidentiality for the function of the transaction. Main findings support that cryptography is the cornerstone technology for blockchain security, but it has to be tailored to meet new challenges. Development in post-quantum algorithms and the infusion of homomorphic encryption will soon become imperative for quantum threats. This paper strongly advocates hybrid solutions that would bring traditional ways merged with novelties, which will provide sustainability over time for digital assets. Thus, this article will be useful for Developers of Blockchain Systems, Cryptographers, Cybersecurity Experts, & Regulators willing to know how protection methods for digital assets evolve.
Yanqi Zhao, Minghong Sun, Min Xie, Xiaoyi Yang · 5 authors
As online application services evolve, an increasing number of users are opting for subscription-based or paywall models to access high-quality content. Anonymous counting tokens (ACTs), which regulate user access while protecting user privacy, are widely adopted in the online paywall model. However, the centralized server of ACT may lead to a single point of failure, thereby exposing users’ privacy. To address this challenge, in this paper, we propose threshold anonymous counting tokens with batch proofs (ThrACT) that balance privacy preservation and access count limitation for online paywalls. We define the system model for ThrACT and provide its concrete construction. We utilize the threshold Boneh-Boyen signature to facilitate distributed issuance of anonymous tokens and enable batch issuance. In addition, our ThrACT employs non-interactive zero-knowledge proofs to verify the label and token requests while allowing the correctness of multiple blind token shares to be validated simultaneously. We also prove that ThrACT satisfies unforgeable and unlinkable security properties. Finally, we evaluate the computational cost of our ThrACT and compare it with other schemes. The experiment result demonstrates that ThrACT not only supports distributed issuance, batch verification, and counting functionalities but also achieves computational overhead in milliseconds. In particular, when the threshold is set to (3,5), the token issuance time is approximately 9 milliseconds.
Maninder Singh, William Bjorndahl, Gagangeet Singh Aujla, Joseph Camp
In the era of continuously increasing demand for bandwidth and revolutionary wireless technologies, efficient spectrum management is essential. This paper proposes a novel multi-tier tokenization approach for dynamic spectrum management. Leveraging the concept of heterogeneous tokenization of spectrum bands, we develop a decentralized framework based on blockchain technology that enables the sharing of spectrum among users. The spectrum space is represented by multi-planes, the first plane consists of unique spectrum bands converted into NFTs for long-term allocations, while the second plane involves subdividing these NFT spectrum bands for short-term usage by retail users through fungible tokens. The fungible tokens are dynamically traded and mapped using particle swarm optimization (PSO) to manage demand and supply. The paper presents formal models of the involved entities and algorithms for creating multi-tier tokens, dynamic token trading and demand-supply mapping using PSO. To enhance privacy, a zero-knowledge proof (ZKP) based approach is employed for user authentication. The proposed framework offers a secure, transparent, and scalable solution for spectrum management, addressing the limitations of traditional centralized approaches. Simulation results demonstrate the effectiveness of the framework in dynamic spectrum access, while providing privacy-aware and scalable solutions suitable for future wireless networks, including 6G.
Recent years have seen great improvements in zero-knowledge proofs (ZKPs). Among them, zero-knowledge SNARKs are notable for their compact and efficiently-verifiable proofs, but suffer from high prover costs. Wu et al. (Usenix Security 2018) proposed to distribute the proving task across multiple machines, and achieved significant improvements in proving time. However, existing distributed ZKP systems still have quasi-linear prover cost, and may incur a communication cost that is linear in circuit size. In this paper, we introduce HyperPianist. Inspired by the state-of-the-art distributed ZKP system Pianist (Liu et al., S&P 2024) and the multivariate proof system HyperPlonk (Chen et al., EUROCRYPT 2023), we design a distributed multivariate polynomial interactive oracle proof (PIOP) system with a linear-time prover cost and logarithmic communication cost. Unlike Pianist, HyperPianist incurs no extra overhead in prover time or communication when applied to general (non-data-parallel) circuits. To instantiate the PIOP system, we adapt two additively-homomorphic multivariate polynomial commitment schemes, multivariate KZG (Papamanthou et al., TCC 2013) and Dory (Lee et al., TCC 2021), into the distributed setting, and get HyperPianistKand HyperPianistDrespectively. Both systems have linear prover complexity and logarithmic communication cost; furthermore, HyperPianistDrequires no trusted setup. We also propose HyperPianist+, incorporating an optimized lookup argument based on Lasso (Setty et al., EUROCRYPT 2024) with lower prover cost. Experiments demonstrate HyperPianistKand HyperPianistDachieve speedups of 63.1x and 40.2x over HyperPlonk with 32 distributed machines. Compared to Pianist, HyperPianistKcan be 2.9x and 4.6x as fast and HyperPianistDcan be 2.4x and 3.8x as fast, on vanilla gates and custom gates respectively. With layered circuits, HyperPianistKis up to 5.9x as fast on custom gates, and HyperPianistDachieves a 4.7x speedup.
Verifying image provenance has become an important topic, especially in the realm of news media. To address this issue, the Coalition for Content Provenance and Authenticity (C2PA) developed a standard to verify image provenance that relies on digital signatures produced by cameras. However, photos are usually edited before being published, and a signature on an original photo cannot be verified given only the published edited image. In this work, we describe VerITAS, a system that uses zero-knowledge proofs (zk-SNARKs) to prove that only certain edits have been applied to a signed photo. While past work has created image editing proofs for photos, VerITAS is the first to do so for realistically large images (30 megapixels). Our key innovation enabling this leap is the design of a new proof system that enables proving knowledge of a valid signature on a large amount of witness data. We run experiments on realistically large images that are more than an order of magnitude larger than those tested in prior work. In the case of a computationally weak signer, such as a camera, we are able to generate a proof of valid edits for a 90 MB image in just over thirteen minutes, costing about $0.54 on AWS per image. In the case of a more powerful signer, we are able to generate a proof of valid edits for a 90 MB image in just over three minutes, costing only $0.13 on AWS per image. Either way, proof verification time is less than a second. Our techniques apply broadly whenever there is a need to prove that an efficient transformation was applied correctly to a large amount of signed private data.
William Bjorndahl, Maninder Singh, Farhad Nouri, Joseph Camp
The ever-growing demand for wireless bandwidth necessitates more flexible and efficient spectrum management techniques than those offered by traditional static allocations. This paper proposes an agent for transparent spectrum management empowered by integrating blockchain-based tokenization and metaheuristic optimization for dynamic spectrum management. The agent facilitates the use of Non-Fungible Tokens (NFTs) for long-term ownership of large spectrum blocks and Fungible Tokens (FTs) for fine-grained, short-term leasing of sub-blocks to smaller-scale users. A particle swarm optimization (PSO) algorithm matches supply to demand, providing efficient and fair resource allocation while minimizing interference. Additionally, zero-knowledge proofs (ZKPs) ensure user authentication without compromising privacy. The preliminary experimentation are performed on a private Ethereum test network and MATLAB simulations for integrability of these mechanisms.
This work explores the integration of Relationalmodel Multi-Agent System (RMAS) with Zero-Knowledge Proofs (ZKP) to enable verifiable computations in distributed systems. RMAS, based on relational algebra, simplifies multi-agent computations using active databases. By combining RMAS with zkSNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge), we provide a framework for privacy-preserving and verifiable operations in Cyber-Physical Systems (CPS). We demonstrate how SQL (Structured Query Language) queries can be transformed into relational algebra and compiled into ZoKrates Domain-Specific Language (DSL) for ZKP generation. A case study in sustainable food supply chains highlights the approach's potential to enhance trust, scalability, and security in collaborative environments.
With the rise of machine learning techniques, ensuring the fairness of decisions made by machine learning algorithms has become of great importance in critical applications. However, measuring fairness often requires full access to the model parameters, which compromises the confidentiality of the models. In this paper, we propose a solution using zero-knowledge proofs, which allows the model owner to convince the public that a machine learning model is fair while preserving the secrecy of the model. To circumvent the efficiency barrier of naively proving machine learning inferences in zero-knowledge, our key innovation is a new approach to measure fairness only with model parameters and some aggregated information of the input, but not on any specific dataset. To achieve this goal, we derive new bounds for the fairness of logistic regression and deep neural network models that are tighter and better reflecting the fairness compared to prior work. Moreover, we develop efficient zero-knowledge proof protocols for common computations involved in measuring fairness, including the spectral norm of matrices, maximum, absolute value, and fixed-point arithmetic. We have fully implemented our system, FairZK, that proves machine learning fairness in zero-knowledge. Experimental results show that FairZK is significantly faster than the naive approach and an existing scheme that use zero-knowledge inferences as a subroutine. The prover time is improved by 3.1x--1789x depending on the size of the model and the dataset. FairZK can scale to a large model with 47 million parameters for the first time, and generates a proof for its fairness in 343 seconds. This is estimated to be 4 orders of magnitude faster than existing schemes, which only scale to small models with hundreds to thousands of parameters.
This paper presents an implementation of a Self-Sovereign Identity (SSI) framework using Ethereum-based standards to meet the technical requirements of the European Digital Identity (EUDI) Architecture Reference Framework (ARF). By leveraging ERC-734/ERC-735 standards, the proposed eSSI system enables decentralized key management, verifiable claims, and onchain auditability. A case study on the Sepolia testnet demonstrates functional alignment with EUDI goals, while highlighting the need for enhanced privacy mechanisms such as zero-knowledge proofs for full compliance.
Recent advances in Vector Oblivious Linear Evaluation (VOLE) protocols have enabled constant-round, fast, and scalable (designated-verifier) zero-knowledge proofs, significantly reducing prover computational cost. Existing protocols, such as QuickSilver [CCS'21] and LPZKv2 [CCS'22], achieve efficiency with prover costs of 4 multiplications in the extension field per AND gate for Boolean circuits, with one multiplication requiring a O (k log k) -bit operation where k== 128 is the security parameter, and 3–4 field multiplications per multiplication gate for arithmetic circuits over a large field. We introduce JesseQ, a suite of two VOLE-based protocols: JQv1 and JQv2, which advance state of the art. JQv1 requires only 2 scalar multiplications in an extension field per AND gate for Boolean circuits, with one scalar needing a$O(\kappa)$bit operation, and 2 field multiplications per multiplication gate for arithmetic circuits over a large field. In terms of communication costs, JQv1 needs just 1 field element per gate. JQv2 further reduces communication costs by half at the cost of doubling the prover's computation. Experiments show that, compared to the current state of the art, both JQv1 and JQv2 achieve at least 3.9× improvement in the online phase for Boolean circuits. For large field circuits, JQv1 has a similar performance, while JQv2 offers a 1.3× improvement. Additionally, both JQv1 and JQv2 maintain the same communication cost as the current state of the art. No-tably, on the cheapest AWS instances, JQv1 can prove 9.2 tril-lion AND gates (or 5.8 trillion multiplication gates over a 61-bit field) for just one US dollar. JesseQ excels in applications like inner products, matrix multiplication, and lattice problems, delivering 40% – 200% performance improvements compared to QuickSilver. Additionally, JesseQ integrates seamlessly with the sublinear Batchman framework [CCS'23], enabling further efficiency gains for batched disjunctive statements.
Homomorphic Encryption (HE) allows computations on encrypted data without decryption. It can be used where the users' information are to be processed by an untrustful server, and has been a popular choice in privacy-preserving applications. However, in order to obtain meaningful results, we have to assume an honest-but-curious server, i.e., it will faithfully follow what was asked to do. If the server is malicious, there is no guarantee that the computed result is correct. The notion of verifiable HE (vHE) is introduced to detect malicious server's behaviors, but current vHE schemes are either more than four orders of magnitude slower than the underlying HE operations (Atapoor et. al, CIC 2024) or fast but incompatible with server-side private inputs (Chatel et. al, CCS 2024). In this work, we propose a vHE framework ZHE: efficient Zero-Knowledge Proofs (ZKPs) that prove the correct execution of HE evaluations while protecting the server's private inputs. More precisely, we first design two new highly-efficient ZKPs for modulo operations and (Inverse) Number Theoretic Transforms (NTTs), two of the basic operations of HE evaluations. Then we build a customized ZKP for HE evaluations, which is scalable, enjoys a fast prover time and has a non-interactive online phase. Our ZKP is applicable to all Ring-LWE based HE schemes, such as BGV and CKKS. Finally, we implement our protocols for both BGV and CKKS and conduct extensive experiments on various HE workloads. Compared to the state-of-the-art works, both of our prover time and verifier time are improved; especially, our prover cost is only roughly 27–36× more expensive than the underlying HE operations, this is two to three orders of magnitude cheaper than state-of-the-arts.
Objective: The combination of 5G connectivity and edge computing known as 5G Edge, lifts the limitations of the Internet of Medical Things (IoMT) and enables a plethora of authentic healthcare services, including access to medical information and diagnosis. Additionally, there is a chance that malicious insiders using the 5G Edge platform could compromise the security and confidentiality of IoMT data. As a result, end users cannot trust 5G Edge data. Materials and methods: This paper imagines a new hierarchical blockchain edge of things (HBEoT) architecture that would facilitate healthcare applications managed by blockchain at the network edge. Additionally, the article delves into how HBEoT can offer security services such as authenticating users, protecting data, detecting attacks, and managing trust. First, the consensus method PoS generates a block for healthcare data, and its hash values are kept in the blockchain. The Zero Knowledge Proof (ZKP) protocol stores secret information in the blockchain, authenticating healthcare systems for enhanced privacy and security. Results: To ensure immutable data storage, the suggested architecture incorporates 5G Edge servers into a blockchain platform. It prevents unauthorised users from accessing healthcare services by acting as an anonymous authenticator. We assessing the proposed methods efficiency in terms of latency, throughput, communication cost, energy consumption cost and the validation between ZKP prover and verifier. Conclusion: We conduct multiple experiments to evaluate the effectiveness of the suggested framework. To further investigate the quality measures, such as authenticate latency, throughput rate was examined. To fulfil the requirements for a 5G-enabled healthcare system, the research shows that the suggested HBEoT-ZKP performs a decrease in latency of around 1.16 s and an improvement in throughput of approximately 339 tps. Communication and energy cost is evaluated and compared with other conventional methods.
Lukas Sparer, Alexander Neulinger, Rigault Bastien, Artur Gonçalves · 7 authors
As the number of unmanned aerial vehicle (UAV) operations is growing rapidly, the risk of collisions increases significantly, making the coordination and verification of flight path compliance crucial. Since many different stakeholders, such as different UAV service suppliers (USS) and UAV operators are involved in an advanced air mobility (AAM) system, the system shall be decentralized and telemetry data shall be measured by the local community using sensor devices. In order to increase system resilience, sub-components of the system are implemented on a blockchain. Smart contracts are used to check whether a UAV has actually navigated the route specified by the USS pre-flight. Due to the restrictions of the system, the flight plan cannot be publicly revealed. Zero-Knowledge proofs (ZKPs) are unfeasible for this use case due to the high number of transactions and computational effort. Therefore, a novel approach has been developed that crosschecks measured telemetry data of UAV flights with flight plans and verifies the correctness without revealing any sensitive flight information. The verification results of UAV telemetry data can further be used to reward UAV operators for complying with the planned flight path.
Cryptography has played a pivotal role in securing communication across human history. From ancient techniques such as hieroglyphic substitutions and Caesar's cipher to contemporary cryptographic systems like RSA and Elliptic Curve Cryptography, the field has continuously adapted to evolving technological paradigms. This article provides a comprehensive review of the historical development of cryptography, highlighting key milestones from ancient Egypt and Mesopotamia, through the mechanical encryption devices of World War II, to the theoretical foundations established by Claude Shannon. It examines the revolutionary introduction of public-key cryptography and follows developments into the digital era, where blockchain technology and privacy innovations like Zero-Knowledge Proofs have expanded cryptographic applications beyond traditional security roles. The article also explores emerging challenges and innovations, particularly those involving artificial intelligence and quantum computing, considering the implications of quantum threats and the ongoing global efforts to develop quantum-resistant encryption standards.
Decentralized Identity (DID) management is pivotal for data security and privacy-preserving in the digital era, yet existing systems face critical challenges, including single point of failure, privacy leakage, and high computational overhead. To address these limitations, this paper proposes a multi-party verifiable trust validation mechanism based on Verifiable Relation Sharing (VRS). The mechanism skillfully integrates Multi-Verifier Zero-Knowledge proofs (MVZK) with Verifiable Secret Sharing (VSS) to securely share secret attribute vectors among multiple verifiers. This enables the generation of Zero-Knowledge Proof (ZKP) of relationships without revealing the actual data. This mechanism ensures that each verifier obtains partial information, thereby effectively defending against single-point attacks, and reducing computational and communication costs through distributed verification. Experimental results confirm the practicality within DID ecosystems, offering a scalable and privacy-preserving solution for multi-party verification and a foundational framework for secure DID verification in blockchain.
Recent digital transformation across industries has extended the demands for secure cross-domain transactions and data sharing. However, traditional Public Key Infrastructure (PKI)-based systems encounter challenges deriving from implementing centralized identity management setting, such as single-point failures, data silos, and insufficient privacy safeguards. Blockchain-based Decentralized Identity (DID) schemes have emerged as a promising solution to addressing cross-domain authentication challenges. In this work, we have systematically examined DID applications in cross-domain authentication, analyzing core mechanisms, e.g., privacy-preserving techniques, anonymous credentials, and lightweight verification protocols. We also investigate a few key supportive technologies, including Zero-Knowledge Proofs (ZKP) and cryptographic accumulators. Main findings of this work covers identifying consensus mechanism limitations and suggesting future potential research directions.