Blockchain Papers

Shraiyash Pandey, Bharat Bhushan, Alaa Ali Hameed

No abstract is available for this record.

Bertalan Zoltán Péter, Imre Kocsis

Privacy and auditability have been conflicting design requirements for blockchainbased distributed ledgers since the inception of the field.As purpose-built blockchains with permissioned consensus and client access are developing in a broad and diverse range of industries, a specific form of this dichotomy is emerging: the need to audit the handling of regulated on-ledger financial assets, such as central bank digital currencies, while preserving the privacy and confidentiality of transactions as much as possible.This paper proposes a novel, privacy-preserving, noninteractive-zero-knowledge-proof-based protocol for a blockchain-based distributed ledger, to prove conformance with fundamental compliance requirements to external auditing parties.We present an extendable implementation and demonstrate the practicality of the approach.

Kiran K. Garimella, Daniel G. Conway

Abstract Building trust in modern business and in social interactions is a critical need as our networks continue to grow and as we engage deeply with unknown people and companies from various parts of the planet. Zero-Knowledge (ZK) technology is a powerful enabler of this trust. It allows a person to demonstrate they know something, have something, or can do something without revealing the actual information or process. We describe the fundamental concepts of cryptography and ZK, their use and limitations, and discuss how ZK technology can be used from a personal as well as a business perspective.

Sameeksha Prasad, Namita Tiwari, Meenu Chawla, Deepak Singh Tomar

No abstract is available for this record.

Ahmed Mateen Buttar, Muhammad Anwar Shahid, Muhammad Nouman Arshad, Muhammad Azeem Akbar

No abstract is available for this record.

Alexandr Kuznetsov, Alex Rusnak, Anton Yezhov, Dzianis Kanonik · 6 authors

Blockchain technology has emerged as a revolutionary tool in ensuring data integrity and security in digital transactions. However, the current approaches to data verification in blockchain systems, particularly in Ethereum, face challenges in terms of efficiency and computational overhead. The traditional use of Merkle Trees and cryptographic hash functions, while effective, leads to significant resource consumption, especially for large datasets. This highlights a gap in existing research: the need for more efficient methods of data verification in blockchain networks. Our study addresses this gap by proposing an innovative aggregation scheme for Zero-Knowledge Proofs within the structure of Merkle Trees. We develop a system that significantly reduces the size of the proof and the computational resources needed for its generation and verification. Our approach represents a paradigm shift in blockchain data verification, balancing security with efficiency. We conducted extensive experimental evaluations using real Ethereum block data to validate the effectiveness of our proposed scheme. The results demonstrate a drastic reduction in proof size and computational requirements compared to traditional methods, making the verification process more efficient and economically viable. Our contribution fills a critical research void, offering a scalable and secure solution for blockchain data verification. The implications of our work are far-reaching, enhancing the overall performance and adaptability of blockchain technology in various applications, from financial transactions to supply chain management.

Aditya Pathak, Irfan Al‐Anbagi, Howard J. Hamilton

Authentication in low-latency Internet of Things (IoT) networks must satisfy three requirements, namely, high security and privacy preservation, high scalability, and low authentication time. These requirements arise because devices in IoT networks must operate in a secure and scalable manner despite being limited in computational resources. Existing authentication mechanisms focus on the security and privacy of IoT networks but neglect the importance of scalability and authentication time. Therefore, existing authentication mechanisms are unscalable and unsuited to low-latency IoT networks. With a focus on increasing scalability and reducing the authentication time while providing high security and privacy preservation in low-latency IoT networks, we propose a mutual authentication mechanism called Zero-Knowledge Proof-based Privacy-Preserving Mutual Authentication (Z-PMA) for IoT networks. The Z-PMA mechanism utilizes a combination of a zero-knowledge proof, an incentive mechanism, and a permissioned blockchain to provide secure, privacy-preserving, scalable, low-latency authentication for IoT networks. We develop a new approach to address the trade-off between the three requirements for authentication mechanisms for low-latency IoT networks that has the potential to improve the overall performance of these networks. A permissioned blockchain is incorporated in the approach to provide secure and immutable data storage using its distributed and unforgeable ledger. Our experimental results show that the Z-PMA mechanism reduces authentication time than existing state-of-the-art authentication mechanisms, while providing high security and privacy preservation as well as high scalability.

Abdu Salam, Mohammad Abrar, Farhan Amin, Faizan Ullah · 7 authors

In the rapidly advancing domain of smart manufacturing, securing data integrity and preventing unauthorized access are critical challenges. This study introduces a novel approach that synergizes anomaly detection techniques with Zero-Knowledge Proofs (ZKPs) to fortify the security framework of smart manufacturing systems. Our methodology employs a combination of data preprocessing, including statistical imputation and data smoothing, alongside advanced anomaly detection using classification methods and neural networks, particularly focusing on deep learning architectures. The detected anomalies undergo verification through zk-SNARKs, a specialized ZKP scheme, ensuring a robust validation process without compromising data confidentiality. Our findings reveal a notable enhancement in the accuracy of anomaly detection, achieving detection rates of approximately 95% for temperature fluctuations and 90% for pressure irregularities, with a significant reduction in false positives. This performance is markedly superior to traditional methods and aligns closely with the highest efficacy rates reported in contemporary studies. Moreover, the utilization of ZKPs for anomaly verification demonstrated a 98% success rate, ensuring the secure and private verification of anomalies. The integration of anomaly detection with ZKPs presents a significant leap forward in addressing the security vulnerabilities inherent in smart manufacturing. This study not only showcases the effectiveness of our approach in enhancing data security and integrity but also sets a benchmark for future research in creating more resilient and trustworthy industrial operations.

Jerry Huang, Ken Huang, Mudi Xu

No abstract is available for this record.

Thang Viet Doan, Tuan-Dat Trinh

No abstract is available for this record.

Venkata Krishna Bharadwaj Parasaram

Self-sovereign identity models and decentralized, blockchain-based identity management can prevent digital ecosystem data breaches and misuse, the study finds. As digital services proliferate and personal data becomes more valuable, central database-based identity systems expose users to single-point failures, unauthorized access, identity theft, and large-scale breaches. This paper analyzes how decentralized IDs, verifiable credentials, and cryptographic verification reduce middlemen, enable selective disclosure, and promote identity governance privacy. Important academic, industrial, and technical contributions show that blockchain anchors credentials in distributed ledgers rather than institutional repositories, improving authentication, traceability, and tamper resistance while limiting undesired access. Immutable audit trails, user-controlled credentials, and reduced central authority dependency have been touted, but empirical performance data, scalability, interoperability, and comparative evaluations of public and permissioned blockchain environments are lacking. These findings explain self-sovereign identity architecture, which lets trusted authority issue credentials but users store and control them directly through digital wallets utilizing cryptographic proofs instead of database lookups. Users can control or withdraw data sharing while maintaining identity. Transparency, limited disclosure, and contextual data presentation prevent cross-platform tracking and increase user autonomy. The research shows how zero-knowledge proofs and predicate-based validation verify credentials without disclosing sensitive data, protecting privacy. Birthdates and locations are not needed to verify age- and location-based limits. SSI master key-derived domain-specific identities reduce correlation hazards and prevent service surveillance. Consent-based sharing, selective disclosure, and cryptographic compartmentalization decrease data collection and profiling. Decentralised blockchain verification maintains credentials usable when the issuer is offline, preventing service disruptions and third-party participation.

Kateryna Kuznetsova, Anton Yezhov

The paper elucidates the fundamental concepts of blockchain technology and its essential parameters, delving into the contemporary scalability challenges faced by blockchain networks. It studies existing directions and compares well-known protocols to propose the solution for the blockchain scalability problem. The main goal of this research is to propose a promising method to solve the scalability problem in blockchain technology. This proposed solution should be universal and applicable in different systems. We chose zero-knowledge proof technology as a promising direction for detailed study. We used protocols, based on this technology, to develop a validation system for a linked chain of blocks. Presented experimental results substantiate the prospects of this direction for solving the scalability problems of modern blockchain systems. The relevance of the chosen topic is determined by the mass introduction of blockchain systems in various areas of human life. As it happens to every network, the volume of information that must be continuously processed increases. This challenge demands to develop solutions to improve systems, making them flexible in working with millions of users. At the same time, it is still important to maintain the security and confidentiality of the information and keep the decentralized organization of the data exchange process in the updated systems. Therefore, in the modern blockchain industry, the predominant challenge revolves around discovering models and methods to overcome the scalability hurdle, facilitating the widespread implementation of blockchain applications on a full scale.

Liqun Chen, Changyu Dong, Christopher J. P. Newton, Yalan Wang

Group signatures and their variants have been widely used in privacy-sensitive scenarios such as anonymous authentication and attestation. In this paper, we present a new post-quantum group signature scheme from symmetric primitives. Using only symmetric primitives makes the scheme less prone to unknown attacks than basing the design on newly proposed hard problems whose security is less well-understood. However, symmetric primitives do not have rich algebraic properties, and this makes it extremely challenging to design a group signature scheme on top of them. It is even more challenging if we want a group signature scheme suitable for real-world applications, one that can support large groups and require few trust assumptions. Our scheme is based on MPC-in-the-head non-interactive zero-knowledge proofs, and we specifically design a novel hash-based group credential scheme, which is rooted in the SPHINCS+ signature scheme but with various modifications to make it MPC (multi-party computation) friendly. The security of the scheme has been proved under the fully dynamic group signature model. We provide an implementation of the scheme and demonstrate the feasibility of handling a group size as large as 2 60 . This is the first group signature scheme from symmetric primitives that supports such a large group size and meets all the security requirements.

Zijian Bao, Debiao He, Qi Feng, Min Luo · 5 authors

A verifiable timed signature (VTS) scheme allows a signature to be time-locked to a known message for a predetermined duration denoted as$\mathsf {T}$. Verifiability ensures that anyone can verify that the time-lock contains a valid signature without completing the computation. In this paper, we introduce a novel VTS construction method based on the RSA group, designed to maintain a constant level of size. This approach serves as an improvement over the previous linear level size construction method (CCS 2020). First, we construct it by using a commitment to a valid RSA signature. This commitment can only be opened to a regular RSA signature after a sequential computation period. Our scheme utilizes a trapdoor verifiable delay function, RSA signatures, and a specialized zero-knowledge proof to instantiate the proposed scheme. We also conduct proofs in three aspects: correctness, soundness, and security. Furthermore, we identify potential applications for VTS and present a simple Bitcoin voting protocol based on an open vote protocol by utilizing VTS. Experimental results show that our scheme is more efficient compared to the construction of VTS (CCS 2020), reducing the signature size by at least 90.5% and lowering computational costs by at least 77%.

Byeongchan Park, Se‐Young Jang, Seok-Yoon Kim, Youngmo Kim

Due to the Corona-19 pandemic phenomenon, various video service platforms that provide OTT (Over The Top) services such as 'Netflix' have achieved rapid growth.OTT platforms that provide such video content do not disclose the viewing time of the content watched by users due to various issues such as personal information protection, so stakeholders are conducting third-party research on usage patterns.While an objective and reliable third-party method of investigating usage patterns is needed, efforts to protect personal information are also needed in the process.The information required for viewership surveys to investigate usage patterns only requires information about what content is used and to what extent, and does not require personal information about users.In this paper, we propose a method to generate and verify the generated usage information by de-identification using zero-knowledge proof protocol when a user selects a specific OTT platform and uses content through an OTT player agent that provides OTT services.

Sri Kanth Mandru

Conventionally, organizations have used Privileged Access Management (PAM) techniques to secure, control, and monitor access to their critical information and resources. The PAM concepts have envisioned designing protocols that help protect user accounts that are deemed to have access to sensitive data ?the most valuable asset of a business. While in the past these techniques have proven vital to data protection and security, the onset of increasingly sophisticated technologies and more determined malicious actors warrants a change of data control and privacy strategies. It becomes impossible to secure a system to achieve 100 percent efficiency. Any system that is attached to the internet is vulnerable to cyberattacks. Hackers have numerous ways to compromise systems if traditional boundary security mechanisms are deployed. Detecting an intrusion in such a setup becomes increasingly challenging if an attacker successfully breaches that boundary layer of defense. Since traditional authentication and authorization might not be reliable in network systems, the zero - knowledge proof model comes in handy. Adding the zero - knowledge proof to the PAM to authenticate users or members and disclose or anonymize them through decentralized identifiers helps in solving the identification and privacy protection problem. We propose a PAM and zero - knowledge proof - inspired approach to address the authentication, data security, and privacy concerns. A zero - knowledge proof is a method that allows the prover to prove to the verifier that they know a certain information without disclosing it.

Ghazaleh Keshavarzkalhori, Cristina Pérez‐Solà, Guillermo Navarro‐Arribas, Jordi Herrera‐Joancomartí · 5 authors

Federated learning (FL) has emerged as an alternative to traditional machine learning in scenarios where training data is sensitive. In federated learning, training is held at end devices, and thus data does not need to leave users devices. However, most approaches to federated learning rely on a central server to coordinate the learning process which, in turn, introduces its own security and privacy problems. We propose Federify, a decentralized federated learning framework based on blockchain which employs homomorphic encryption and zero knowledge proofs to provide security, privacy, and transparency. The scheme preserves the confidentiality of both the data used for training and the local models using homomorphic encryption. zkSNARKs are used to provide security by verifying the contributions from the different agents, and transparency of both the learning process and the incentive mechanism is achieved by delegating coordination into a smart contract in a public blockchain. We have also implemented, deployed, and evaluated a proof of concept of our framework, to demonstrate its viability both in terms of computational resources needed and cost to train in a public generic blockchain such as Ethereum.

Jinsheng Yang, Wenfeng Zhang, Zhaohui Guo, Zhen Gao

Federated learning is a privacy-preserving machine learning framework where multiple data owners collaborate to train a global model under the orchestra of a central server. The local training results from trainers should be submitted to the central server for model aggregation and update. Busy central server and malicious trainers can introduce the issues of a single point of failure and model poisoning attacks. To address the above issues, the trusty decentralized federated learning (called TrustDFL) framework has been proposed in this paper based on the zero-knowledge proof scheme, blockchain, and smart contracts, which provides enhanced security and higher efficiency for model aggregation. Specifically, Groth 16 is applied to generate the proof for the local model training, including the forward and backward propagation processes. The proofs are attached as the payloads to the transactions, which are broadcast into the blockchain network and executed by the miners. With the support of smart contracts, the contributions of the trainers could be verified automatically under the economic incentive, where the blockchain records all exchanged data as the trust anchor in multi-party scenarios. In addition, IPFS (InterPlanetary File System) is introduced to alleviate the storage and communication overhead brought by local and global models. The theoretical analysis and estimation results show that the TrustDFL efficiently avoids model poisoning attacks without leaking the local secrets, ensuring the global model’s accuracy to be trained.

Abusaid Manap, Gulnara Abitova, Gulzhan Uskenbayeva, Aigul Shaikhanova

In the era of pervasive digital data, ensuring secure file storage has become a paramount concern. This paper explores the significance of hybrid cryptography in the development of information technology for secure file storage. Hybrid cryptography, combining symmetric and asymmetric encryption, offers robust protection against unauthorized access, tampering, and data loss. The article reviews recent cryptography literature, highlighting the importance of secure file storage in today's interconnected world and examining the benefits of hybrid cryptography. The analysis of articles on cryptography reveals emerging trends and challenges. Post-quantum cryptography addresses concerns about quantum threats, while blockchain-based cryptography enhances security in IoT data sharing. Homomorphic encryption enables computations on encrypted data, and privacy-preserving cryptographic protocols facilitate secure multi-party computation. Machine learning's intersection with cryptanalysis introduces efficiency but raises ethical considerations. The paper further discusses advancements and trends in cryptography techniques, including post-quantum cryptography, homomorphic encryption, zero-knowledge proofs, post-quantum key exchange, secure multi-party computation, and post-quantum signature schemes. These developments aim to ensure long-term security against quantum attacks, enable privacy-preserving computations, and enhance the confidentiality, integrity, and authentication of digital communication and data storage. In conclusion, the paper advocates for the adoption of hybrid cryptography in secure file storage systems. Its combination of symmetric and asymmetric encryption, along with its adaptability to evolving security landscapes, positions hybrid cryptography as a formidable approach to data protection. By embracing hybrid cryptography and staying informed about the latest advancements, organizations can navigate the digital age with confidence, ensuring the confidentiality, integrity, and availability of stored files.

Jinrui Sha, Shengli Liu

No abstract is available for this record.

Rafael Belchior, Dimo Dimov, Zahary Karadjov, Jonas Pfannschmidt · 6 authors

The field of blockchain interoperability plays a pivotal role in blockchain adoption. Despite these advances, a notorious problem persists: the high number and success rate of attacks on blockchain bridges. We propose Harmonia, a framework for building robust, secure, efficient, and decentralized cross-chain applications. A main component of Harmonia is DendrETH, a decentralized and efficient zero-knowledge proof-based light client. DendrETH mitigates security problems by lowering the attack surface by relying on the properties of zero-knowledge proofs. The DendrETH instance of this paper is an improvement of Ethereum’s light client sync protocol that fixes critical security flaws. This light client protocol is implemented as a smart contract, allowing blockchains to read the state of the source blockchain in a trust-minimized way. Harmonia and DendrETH support several cross-chain use cases, such as secure cross-blockchain bridges (asset transfers) and smart contract migrations (data transfers), without a trusted operator. We implemented Harmonia in 9K lines of code. Our implementation is compatible with the Ethereum Virtual Machine (EVM) based chains and some non-EVM chains. Our experimental evaluation shows that Harmonia can generate light client updates with reasonable latency, costs (a dozen to a few thousand US dollars per year), and minimal storage requirements (around 4.5 MB per year). We also carried out experiments to evaluate the security of DendrETH. We provide an open-source implementation and reproducible environment for researchers and practitioners to replicate our results.

Irina Strelkovskaya, Oleksiy Onatskiy, Larysa Yona

Background. To ensure the protection of the biometric access control system used in unsecured communication channels, it is necessary to exclude the storage and transfer, transfer of biometric data as well as sequences generated on their basis. The paper proposes a cryptographic protocol of two-factor authentication with the zero-knowledge over the extended field GF(2m) on elliptic curves using biometric data and the private key of the user. Objective. The aim of the article is to develop a cryptographic protocol for zero-knowledge two-factor authentication based on elliptic curves using biometric data and the user’s private key, which allows increasing cryptographic strength and reducing the duration of the authentication process. Methods. The process of implementing zero-knowledge proof protocols is as follows: one user (proofer) can convince another user (verifier) that he has some secret without disclosing the secret itself. Results. A cryptographic protocol for two-factor authentication with zero-knowledge over the extended field GF(2m) of elliptic curves using user biometric data is proposed, which significantly reduces the size of the protocol parameters and increases cryptographic strength (computational complexity of the breaking). There is no leakage of private key information and biometric data of the user during the execution of the zero-knowledge proof protocol. Conclusions. The implementation of a cryptographic protocol with zero-knowledge proof two-factor authentication based on elliptic curves allows significantly reducing the size of protocol parameters and increasing the cryptographic strength (computational complexity of the breaking).

Ірина Стрелковська, Олексій Онацький, Лариса Григорівна Йона

Background. To ensure the protection of the biometric access control system used in unsecured communication channels, it is necessary to exclude the storage and transfer, transfer of biometric data as well as sequences generated on their basis. The paper proposes a cryptographic protocol of two-factor authentication with the zero-knowledge over the extended field GF(2m) on elliptic curves using biometric data and the private key of the user. Objective. The aim of the article is to develop a cryptographic protocol for zero-knowledge two-factor authentication based on elliptic curves using biometric data and the user’s private key, which allows increasing cryptographic strength and reducing the duration of the authentication process. Methods. The process of implementing zero-knowledge proof protocols is as follows: one user (proofer) can convince another user (verifier) that he has some secret without disclosing the secret itself. Results. A cryptographic protocol for two-factor authentication with zero-knowledge over the extended field GF(2m) of elliptic curves using user biometric data is proposed, which significantly reduces the size of the protocol parameters and increases cryptographic strength (computational complexity of the breaking). There is no leakage of private key information and biometric data of the user during the execution of the zero-knowledge proof protocol. Conclusions. The implementation of a cryptographic protocol with zero-knowledge proof two-factor authentication based on elliptic curves allows significantly reducing the size of protocol parameters and increasing the cryptographic strength (computational complexity of the breaking).

Jonas Groß

Many central banks worldwide are considering issuing a retail central bank digital currency due to the decreasing use of cash and the emergence of new forms of digital money. One of the main topics of debate is the level of transaction privacy. While technology allows for complete privacy or transparency, a high degree of privacy is necessary for a central bank digital currency for economic, regulatory, and socioeconomic reasons. The private sector has failed to provide a privacy-preserving payment solution. This chapter proposes a software-based central bank digital currency approach that uses zero-knowledge proofs to ensure complete transaction privacy while adhering to anti-money laundering regulations. Experts from central banks, corporations, associations, and academia have evaluated the approach and found it to be a feasible and promising solution for a privacy-preserving and compliant central bank digital currency.