The rapid advancement of digital services and online interactions has highlighted the need for secure, user-centric identity management systems. Traditional identity solutions, often centralized and dependent on trusted third parties, pose challenges related to privacy, security, and control over personal data. Distributed Ledger Technology (DLT), particularly blockchain, offers a promising solution for decentralized identity management by enabling self-sovereign identities (SSI). Through the use of decentralized identifiers (DIDs) and verifiable credentials (VCs), DLT allows individuals to maintain full control over their personal information, eliminating the need for intermediaries while ensuring data integrity and privacy. This paper explores the key principles of DLT-based decentralized identity management, discussing its potential to enhance privacy, security, and interoperability in digital ecosystems. We examine the various technical frameworks, challenges, and standards in the field, with a focus on the integration of DLT with emerging technologies such as zero-knowledge proofs (ZKPs) and secure multiparty computation (SMPC). Additionally, we evaluate real-world use cases, from financial services to healthcare, and the role of regulatory frameworks in shaping the future of decentralized identity systems. Ultimately, DLT presents a paradigm shift in identity management, offering scalable, transparent, and trusted solutions for the digital age.
Purpose The growing concern over privacy leakage has led to reduced user participation in data sharing, prompting the exploration of novel techniques such as federated learning (FL). Meanwhile, existing FL solutions often overlook the validation of the training process, leaving room for malicious trainers to introduce false or toxic local models, detrimental to the global model’s utility. This study aims to propose a zero-knowledge proof-based verifiable federated learning (ZKP-FL) framework on the blockchain. Design/methodology/approach ZKP-FL leverages zero-knowledge proofs to verify the extensive local training process without threatening the local privacy. To reduce the memory and runtime overhead, the authors divide the training algorithm to be proven into smaller pieces and generating proofs for each segment. The authors leverage sigma-protocol to ensure the consistency and reliability of these proofs. Moreover, they design a secure model aggregation protocol that matches the local proofs, safeguarding the data privacy of individual local models throughout the process. Furthermore, this aggregation protocol can also guarantee the correctness of the aggregation. Findings To establish the effectiveness and security of ZKP-FL, the authors conduct a formal security analysis in terms of completeness, soundness and zero-knowledge properties. Experimental evaluations with different algorithms and models within the ZKP-FL framework demonstrate that with parallel execution the additional proof time per round is minimal. Originality/value This paper offers a novel perspective on security and privacy of FL, providing valuable insights that extend the current understanding of verifiable FL. The findings contribute to the ZKP-FL, highlighting areas for future research and practical applications.
With the diversity of data generated in daily life and the high economic benefits of effective use of data in various aspects, data trading has become a trend, and the fairness of data trading has also received increasing attention in recent years. Fairness means that the buyer and seller either get what they want or neither, which is one of the most basic requirements of transactions. Studies have shown that it is difficult to design a fair agreement based on buyers and sellers alone. Therefore, existing fair agreements generally rely on Trusted Third Parties (TTP) for transactions, and their fairness is based on the behavior of TTP and the trust of both parties in TTP. After the emergence of blockchain and smart contracts, their decentralization and transparency make them excellent candidates for replacing TTP. Therefore, this paper attempts to design a secure and fair data transaction protocol based on smart contracts. In order to ensure the security of data, we use an advanced Passive Proxy Re-Encryption (PPRE) scheme to enable the smart contract to transfer the decryption right to the buyer after receiving the buyer’s payment. In addition, based on smart contracts and PPRE, a fair protocol for data trading is proposed, and the fairness of the protocol is guaranteed by an arbitration protocol. The protocol supports ciphertext publicity and repeatable sale, thereby reducing the number of interactions. Comprehensive experimental results verify the feasibility and effectiveness of the proposed protocol.
Traditional voting systems struggle with scalability, security, and transparency, making blockchain a promising solution due to its decentralization and immutability. However, Proof-of-Work (PoW) is inefficient for large-scale voting due to high energy consumption. This project leverages Proof-of-Stake (PoS) as an energy-efficient alternative, ensuring security and scalability. It maintains voter confidentiality, prevents duplicate voting through a one-vote token mechanism, and uses a staked cryptocurrency verification process. Smart contracts automate voter registration, vote validation, and result tabulation, minimizing human error. Performance analysis highlights improvements in transaction speed, adaptability, and fraud prevention, demonstrating PoS as a secure, scalable, and transparent solution for modernizing voting systems while enhancing accessibility and trust.
Damiano Di Francesco Maesa, Matteo Loporchio, Frank Tietze
This paper considers the application scenario of Intellectual Property (IP) management, a business process yet to fully embrace digitisation and the advantages it brings. We propose to leverage Distributed Ledger Technology (DLT) to digitise license agreements management by providing automated and trustworthy royalty computation, transaction execution, and payment distribution. This can be achieved by employing smart licenses, i.e., bundles of smart contracts implementing the royalty logic of license agreements. To provide scalability, flexibility, and resilience, we propose to deploy smart licenses on a network of networks model, i.e., a set of heterogeneous networks potentially running different DLT protocols and connected by cross-chain information exchange protocols. A novel advantage of the network of networks approach is that it allows for the use of private values for royalty computation, which is impossible in the traditional model. Of course, supporting private DLT networks requires privacy-preserving cross-chain schemes, a still open problem in the literature. This is why we present two alternative privacy-preserving cross-chain schemes for our considered application scenario of license agreements management, one based on Homomorphic Encryption (HE) and the other on Zero-Knowledge (ZK) proofs. Besides discussing their theoretical advantages and drawbacks, we present an experimental evaluation of a prototype implementation of smart licenses based on both schemes. • We propose a network of networks model that enhances scalability in smart license ecosystems. • The proposed model allows smart licenses to leverage data from heterogeneous networks, including private ones. • We compare two methods for privacy-preserving cross-chain communication: homomorphic encryption and zero-knowledge proofs. • We experimentally evaluate and compare two different privacy-preserving smart license implementations.
This paper introduces a certificate verification system powered by blockchain technology to prevent document forgery and ensure authenticity. By using a distributed ledger, the system creates a permanent and transparent record for issuing and verifying certificates. In this Block chain technology, block chain performs Secure Certificate Storage with hash encryption, real time data verification & decentralized network of nodes validation. By using block chain technology, we can prevents Forgery from tampering and ensure authenticity. It ensures the data integrity while doing real time verification and it is more efficient than other technology. It minimizes the verification cost. This application is more scalable and used in multiple areas like the educational sector for document verification and health industry to validate the medical records and Supply chain management. This project demonstrates the potential of blockchain technology in securing certificate verification, preventing forgery, and enhancing trust in document authenticity.
ABSTRACT Self‐sovereign identity management systems operate in open network environments and face security threats from semi‐trusted or malicious adversary models. In such environments, verifiable credentials are susceptible to attacks such as theft and forgery. In response to the privacy risks associated with verifiable credentials during issuance and revocation, this article proposes a privacy protection scheme for user information during the issuance and revocation processes of verifiable credentials in self‐sovereign identity management based on blockchain technology. First, a privacy‐preserving method that does not rely on a single identity provider and resists Sybil attacks has been designed using secure multi‐party computation cryptographic techniques. Second, the consortium blockchain committee nodes act as the issuer of verifiable credentials. By combining attribute commitments and zero‐knowledge proof techniques, the user's identity information is hidden, achieving the privacy protection goal during the issuance of verifiable credentials. Furthermore, in order to protect user privacy during the revocation of verifiable credentials (VCs), we employ a cryptographic accumulator technique to implement the revocation operation. This approach ensures the security of user privacy while effectively managing the revocation of credentials. Finally, this paper conducts a security analysis and performance evaluation of the proposed scheme. The results show that our scheme strikes a balance between security needs and time efficiency.
The integration of privacy-preserving transactions into public blockchains such as Ethereum remains a major challenge. The Stealth Address Protocol (SAP) provides recipient anonymity by generating unlinkable stealth addresses. Existing SAPs, such as the Dual-Key Stealth Address Protocol and the Curvy Protocol, have shown significant improvements in efficiency, but remain vulnerable to quantum attacks. Post-quantum SAPs based on lattice-based cryptography, such as the Module-LWE SAP, on the other hand, offer quantum resistance while achieving better performance. In this paper, we present a novel hybrid SAP that combines the Curvy protocol with the computational advantages of the Module-LWE technique while remaining Ethereum-friendly. In contrast to full post-quantum solutions, our approach does not provide quantum security, but achieves a significant speedup in scanning the ephemeral public key registry, about three times faster than the Curvy protocol. We present a detailed cryptographic construction of our protocol and compare its performance with existing solutions. Our results prove that this hybrid approach is the most efficient Ethereum-compatible SAP to date.
This work proposes the Trust Based Proof of Authority as a potential solution for achieving security, scalability, and efficiency in blockchain enabled Industry 5.0 IoT networks. Trust levels are assigned to validators in accordance to their trust, their contribution in the past, and their system reliability metrics. Only nodes with high trust level perform block validation which greatly enhances security. In addition, this approach is more efficient and energy conserving than existing consensus mechanisms such as Proof of Stake or standard PoA. The proposed method is implemented using IoT integrated healthcare system and tested using iFogSim simulator and the Ethereum blockchain environment. Several key performance metrics such as block validation time, accuracy of validation, throughput of the system, processing time, and scalability have been used to evaluate the performance of the proposed system. Experimental results proved that the validation of block due to the Trust-Based PoA mechanism, leading to reduced computational overhead and improving reliability of the system. The proposed TB-PoA is appropriate for secure and scalable IoT applications within the Industry 5.0.
Zero-Knowledge Proofs (ZKPs) are a rapidly growing technique for privacy-preserving and verifiable computation.ZKPs enable one party (a prover: P) to prove to another (a verifier: V) that a statement is true or correct without revealing any additional information.This powerful capability has led to ZKPs being applied and proposed for application in blockchain technologies, verifiable machine learning, and electronic voting.However, ZKPs have yet to see widespread, ubiquitous adoption due to the exceptionally high computational complexity of the proving process.Naturally, there has been recent work to accelerate ZKP primitives and protocols using GPUs and ASICs.However, the protocols considered so far face one of two challenges: they require a trusted setup for each new application or generate large proofs with high verification costs, limiting their applicability in scenarios with numerous verifiers or strict verification time constraints.HyperPlonk is a state-of-theart ZKP protocol that supports both one-time, universal setup and small proof sizes/verification costs expected by publicly verifiable, consensus-based systems (e.g., blockchain).While HyperPlonk's setup and verifier properties are highly desirable, the proving phase is costly.A HyperPlonk prover must compute on large bitwidths (e.g., 255-381b) and polynomials (e.g., of degree 2 24 ), employs computationally (e.g., MSM) and bandwidth (e.g., SumCheck) intensive kernels, and the complete protocol comprises many steps, each constituting distinct kernels.We present an accelerator, zkSpeed, to
The seminal work of Goldreich and Krawczyk (SIAM Journal on Computing) shows that any constant-round public-coin interactive proof for languages not in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mi mathvariant="sans-serif">B</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> </mml:mrow> </mml:mrow> </mml:math> cannot be black-box zero knowledge. Their result says nothing, however, about proofs (or arguments) of knowledge for languages in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mi mathvariant="sans-serif">B</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> </mml:mrow> </mml:mrow> </mml:math>. As a special case, their work leaves open the question of whether Schnorr's protocol for proving knowledge of discrete logarithms in cyclic groups is black-box zero knowledge. In this work we focus on the zero knowledge of proofs of knowledge, centering on Schnorr's protocol as a prominent example. We prove two lower bounds, ruling out two different classes of simulators through which Schnorr's protocol can be proven zero knowledge: We prove that if a relation <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>ℛ</mml:mi> </mml:mrow> </mml:math> has a public-coin interactive proof of knowledge that is black-box zero knowledge and this protocol is compatible with the Fiat-Shamir transform in the random oracle model, then <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>ℛ</mml:mi> </mml:mrow> </mml:math> must be efficiently searchable. As an immediate corollary, we deduce that Schnorr's protocol cannot be black-box zero knowledge in groups in which discrete log is hard. We define a new class of simulators for Schnorr's protocol, which we call generic simulators. A generic simulator is one that works in any cyclic group, and does not use the representation of the specific group in which Schnorr's protocol is instantiated. We prove that Schnorr's protocol cannot have generic simulators. As an additional contribution, we generalize the original lower bound of Goldreich and Krawczyk, to prove that a language not in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mi mathvariant="sans-serif">B</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> <mml:mi mathvariant="sans-serif">P</mml:mi> </mml:mrow> </mml:mrow> </mml:math> cannot have an interactive proof (not necessarily of knowledge) that is both black-box zero knowledge and compatible with the Fiat-Shamir transform in the random oracle model. In conjunction with recent works, this extends the Goldreich-Krawczyk lower bound to public-coin protocols that are not constant-round but have round-by-round soundness, including the parallel repetition of any public-coin interactive proof.
Michele Orrù, George Kadianakis, Mary Maller, Greg Zaverucha
A fundamental challenge in zero-knowledge proof systems is implementing operations that are “foreign” to the underlying constraint system, in that they are arithmetic operations with a different modulus than the one used by the proof system. The modulus of the constraint system is a large prime, and common examples of foreign operations are Boolean operations, field arithmetic, or public-key cryptography operations. We present novel techniques for efficiently embedding such foreign arithmetic in zero-knowledge, including (i) equality of discrete logarithms across different groups; (ii) scalar multiplication without requiring elliptic curve operations; (iii) proving knowledge of an AES encryption. Our approach combines rejection sampling, sigma protocols, and lookup protocols. We implement and provide concrete benchmarks for our protocols.
Justin A. Drake, Dmitry Khovratovich, Mikhail Kudinov, Benedikt Wagner
With the threat posed by quantum computers on the horizon, systems like Ethereum must transition to cryptographic primitives resistant to quantum attacks. One of the most critical of these primitives is the non-interactive multi-signature scheme used in Ethereum's proof-of-stake consensus, currently implemented with BLS signatures. This primitive enables validators to independently sign blocks, with their signatures then publicly aggregated into a compact aggregate signature. In this work, we introduce a family of hash-based signature schemes as post-quantum alternatives to BLS. We consider the folklore method of aggregating signatures via (hash-based) succinct arguments, and our work is focused on instantiating the underlying signature scheme. The proposed schemes are variants of the XMSS signature scheme, analyzed within a novel and unified framework. While being generic, this framework is designed to minimize security loss, facilitating efficient parameter selection. A key feature of our work is the avoidance of random oracles in the security proof. Instead, we define explicit standard model requirements for the underlying hash functions. This eliminates the paradox of simultaneously treating hash functions as random oracles and as explicit circuits for aggregation. Furthermore, this provides cryptanalysts with clearly defined targets for evaluating the security of hash functions. Finally, we provide recommendations for practical instantiations of hash functions and concrete parameter settings, supported by known and novel heuristic bounds on the standard model properties.
Suhyeon Lee, Euisin Gee, Najmeh Soroush, Muhammed Ali Bingol · 5 authors
Simple commit-reveal beacons are vulnerable to last-revealer strategies, and existing descriptions often leave accountability and recovery mechanisms unspecified for practical deployments. We present Commit-Reveal$^2$, a layered design for blockchain deployments that cryptographically randomizes the final reveal order, together with a concrete accountability and fallback mechanism that we implement as smart-contract logic. The protocol is architected as a hybrid system, where routine coordination runs off chain for efficiency and the blockchain acts as the trust anchor for commitments and the final arbiter for disputes. Our implementation covers leader coordination, on-chain verification, slashing for non-cooperation, and an explicit on-chain recovery path that maintains progress when off-chain coordination fails. We formally define two security goals for distributed randomness beacons, unpredictability and bit-wise bias resistance, and we show that Commit-Reveal$^2$ meets these notions under standard hash assumptions in the random-oracle model. In measurements with small to moderate operator sets, the hybrid design reduces on-chain gas by more than 80% compared to a fully on-chain baseline. We release a publicly verifiable prototype and evaluation artifacts to support replication and adoption in blockchain applications.
An E-voting framework utilizing decentralized technology can establish a secure and transparent environment for elections, where voters can confidently cast their ballots knowing that their votes are final and untampered with. Blockchain's decentralized structure ensures that votes are recorded accurately, preventing interference from external actors. In a protected Evoting framework, each vote becomes part of an immutable, distributed ledger, allowing for peer-to-peer validation of transactions. This ensures that each voice counts as the only, unchanging record. The results can be reported immediately as soon as the voting process is completed. Voting is a critical process carried out in democratic societies, usually through secret voting documents or other similar methods. However, traditional voting systems are often plagued by problems such as voting manipulation, low turnout and logistics challenge. To solve these problems, we propose implementation of decentralized voting platforms that offer advanced security, efficiency and confidence in the election process
Open access
2 source records
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Distributed Ledger Technologies (DLTs), including Blockchain, have revolutionized financial systems by offering decentralized, transparent, and secure mechanisms for data management and transactions. However, for these systems to maintain integrity and protect sensitive financial data, robust cryptographic techniques are essential. Cryptography ensures data confidentiality, authenticity, integrity, and non-repudiation, which are critical for the security of financial transactions in DLTs. This article examines the role of cryptographic protocols such as hashing, digital signatures, asymmetric encryption, and zero-knowledge proofs in safeguarding distributed ledgers. Furthermore, we explore their applications in securing financial transactions, preventing fraud, ensuring compliance, and enhancing the overall reliability of DLTs in financial systems. The discussion also delves into the challenges of cryptographic security in the face of emerging threats and the potential impact of quantum computing on existing cryptographic protocols.
B. Anandapadmanaban, Athira V Umesh, A Anilkumar, Arun K. Das · 5 authors
The rapid development of blockchain technology opens up trends and new directions in securing, authenticating and decentralizing data. EduChain allows for two demonstration areas, namely, use of blockchain and NFTs in certification solutions for more reliable certificate checking and certificate storage. Built on Ethereum blockchain and utilizing IPFS, from the perspective of universities, colleges, and other institutions, EduChain facilitates issuance of secure and tamper-proof NFT certificates for sensitive information. It has MetaMask-Like login and easy integration with the Ethereum platform and has several other advanced characteristics. EduChain responds to relevant issues with conventional certification solutions, which include fake certifications and certifications based on fake documents, time-consuming examinations of documents, and insufficient control of one’s own data. Turing tests conducted on Sepolia testnet established that the system provides for immutable, verifiable and decentralized certification. Further improvements could be real-time notifications or other applications that would work in conjunction with Revizto; analysis tools that would produce even more meaningful information. EduChain can be considered as the good example of how using NFTs can improve the processes of documents verification in various sectors.
The protection of personal privacy has become a paramount issue in the field of data science, with its significance continuously rising. Differential privacy technology has garnered significant attention for its effectiveness in preserving individual privacy. However, the implementation of differential privacy relies on a degree of trust in the entities or individuals executing the algorithms. This paper proposes an innovative solution: a verifiable differential privacy mechanism based on zero-knowledge proofs. This approach integrates differential privacy with zero-knowledge proof technology to not only verify the correctness of the differential privacy techniques but also enhance the transparency and reliability of the algorithms. Additionally, we have designed a publicly verifiable data release scheme that integrates commitment mechanisms and range proofs, ensuring that the range of published data noise does not exceed predetermined thresholds, thereby ensuring the utility of the data. Compared to other verifiable differential privacy solutions, our approach is unique in that it does not rely on the number of participants but is solely dependent on the precision of the data. This means that our computational cost will not increase with the addition of more participants. Finally, we conducted a performance evaluation of the solution, which only took 700ms to complete a single verification. On average, there was a 6% reduction in expectation and a 40% reduction in variance, demonstrating the enhancement of its data utility and the feasibility and effectiveness in practical applications.
This article presents a comprehensive framework for implementing privacy-preserving credit card reward systems using Secure Multi-Party Computation (SMPC) technologies. Traditional reward architectures require extensive sharing of sensitive transaction data across multiple entities, creating significant privacy risks, security vulnerabilities, and regulatory compliance challenges. It leverages cryptographic advances to enable card issuers, payment networks, and merchant partners to collaborate on reward calculations,fraud detection, and personalized offers without revealing sensitive transaction details to one another. The article explores the evolution of privacy-preserving technologies in financial systems, comparing Fully Homomorphic Encryption, Zero-Knowledge Proofs, and SMPC approaches. A detailed case study of a travel rewards program implementation demonstrates how this framework ensures data remains protected throughout the entire process while maintaining the performance characteristics necessary for production deployment. The system provides comprehensive privacy protection, enhances fraud detection capabilities through secure collaboration, and facilitates compliance with evolving privacy regulations.Performance evaluations confirm the practical viability of the article, with minimal latency impact, strong scalability characteristics, and robust security guarantees. It contributes to the growing field of privacy-enhancing technologies for financial services and offers a viable solution to balance analytical utility with privacy protection in consumer-facing applications.
This paper presents the translation of regulatory smart contracts written in RegLang into MedTiny, a component-based modeling language tailored for the development and verification of reliable systems. RegLang, a domain-specific language for embedding regulatory requirements in smart contracts, is limited by its users' expertise in smart contract development and formal verification. To address this, we propose an automated code generation method that translates RegLang contracts into MedTiny, enabling domain experts to utilize MedTiny's verification capabilities and modular system architecture. By leveraging MedTiny's toolchain and SMT solvers, we detect redundancies and conflicts in regulations early in the development cycle, helping domain experts avoid introducing unintended behaviors. This approach not only preserves the original specifications of RegLang contracts but also improves overall system reliability by integrating comprehensive verification capabilities. A case study illustrates the practical benefits of this translation, supporting complex rule-based contract management and mitigating the risks associated with regulatory changes.
In this work, we address the evolutionary computation in programmable cryptography on blockchain technologies for the first time in the literature. For that, we propose a novel privacy-preserving and decentralized protocol ([email protected]) where the evolutionary computation model is public while the user inputs/outputs (i.e. the current and next populations) are private. The protocol relies on the transitions between the public-domain (i.e. contract-domain) and the private-domain (i.e. evolutionary-domain) to be secure. We perform an experimental study using two popular benchmark problems to measure the blockchain gas consumption, zero-knowledge proof generation/verification times and zero-knowledge proof size.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques