Blockchain Papers

H. Anwar Basha, R. Sivasubramanian, M. Rajasekhara Babu, P. Anitha · 6 authors

No abstract is available for this record.

Veri, Hans Kristjan

The rise of quantum computing threatens to break many of the cryptographic systems that secure today’s digital world. In response, researchers are developing new tools designed to remain secure in a post-quantum future. Most of the promising candidates for post-quantum digital signatures rely on security assumptions based on lattices or properties of hash functions. Another promising approach transforms secure multi-party computation protocols into zero-knowledge proofs, which are then turned into digital signatures. This technique, known as multi-party computation in-the-head (MPCitH), offers strong security properties and flexibility for distributed applications. This thesis investigates whether MPCitH digital signatures can be efficiently adapted for use by two cooperating parties to jointly produce a signature. Here we show how to construct two-party signatures based on syndrome decoding in-the-head (SDitH) signatures. We propose a provably secure scheme that achieves the smallest known communication overhead among two-party MPCitH signatures, while resulting in a signature size approximately double that of a single-prover variant. This result provides a new data point in the design space of multi-party MPCitH signatures and post-quantum digital signatures in general.

Tianxiang Dai, Yufan Jiang, Yong Li, Jörn Müller‐Quade · 5 authors

In the secure two-party computation (2PC), an adversary is often categorized as semi-honest or malicious, depending on whether it follows the protocol specifications. Covert security (Aumann and Lindell, 2010) first looks into the “middle ground”, such that an active adversary who cheats will be caught with a predefined probability. Other security notions, such as publicly auditable security (Baum et al., 2014) and (robust) accountability family (Küsters et al., 2010; Graf et al., 2023; Rivinius et al., 2022), achieve public verifiability as a stronger security guarantee by relying on heavy offline and online constructions with zero knowledge proofs and (or) a bulletin board functionality. In this work, we propose a new security notion called honorific security, where an external arbiter can identify the cheater without a bulletin board. Specifically, we delay and outsource the verification steps to the arbiter, so that the original online computation is thus accelerated. We show that a maliciously secure garbled circuit (GC) (Yao, 1986) protocol can be constructed with only slightly more overhead than a passively secure protocol. Our construction performs up to 2.37 times and 13.30 times as fast as the state-of-the-art protocols with covert and malicious security, respectively.

Philippe Gaborit, Mercedes Haiech, Romaric Neveu

At a time when post-quantum cryptography is more and more present in the cryptographic landscape, it is of great interest to find new hard problems on which we can rely. Here, we present a new problem, the vector space factorization problem, and use it to build a signature scheme. The idea of factorizing subspaces of a finite field is used in rank metric codes, most notably in the decoding of LRPCs. In this context, one of the subspaces is known to factorize. Factorizing without the knowledge of both subspaces appears in the signature scheme Murave, in which the rank support basis decomposition problem is introduced from a coding theory in rank metric point of view. In Bro's thesis, the SquareSpace problem is introduced, where one wants to find the 'square root' of a subspace. We generalize here this problem into the vector space factorization problem, which is the same as the rank support basis decomposition problem introduced in Murave, the difference being we do not look at it from a coding theory point of view, but really from a vector subspace one. We use it here to build a zero-knowledge proof of knowledge. The scheme uses the MPCitH paradigm, and especially the TCitH framework, which is an efficient way to build ZK proofs. We study the difficulty of solving the vector space factorization problem by detailing the combinatorial attacks on the problem, analyzing their complexity, and describing an algebraic model to solve the problem. We then explain the MPC protocol used to build the signature scheme. Finally, this construction allows us to obtain sizes of signature of 8.9 to 10.9 kB for the first security level defined by NIST, which is reasonable as MPC-in-the-Head signatures typically range from 2.5 kB for an MQ instance to 14 kB for lattice-based instances.

Hiroaki Anada, Masayuki Fukumitsu, Shingo Hasegawa

The group signature with designated traceability (GSdT) is a kind of group signatures (GS) which aim to restrict the opening authority of the group manager; by setting an access structure over openers' attributes at the signing, a signer is able to control openers who can open the signature.A generic construction of GSdT was given when the notion was introduced, then a pairing-based construction and a symmetric-key-based one were presented.Nonetheless, it remains open whether a post-quantum GSdT with full anonymity can be truly constructed.In this paper, we give a lattice-based GSdT scheme that has full anonymity for the first time.In our construction, the lattice-based ciphertext-policy attribute-based encryption (CP-ABE) by Tsabary and the lattice-based group signatures (GS) by Libert et al. are employed.The CP-ABE is based on the Regev public-key encryption, while the GS uses a non-interactive zero-knowledge proof to prove the correctness of the encryption in the signing process.Based on the compatibility, we combine and modify them to build up a GSdT scheme.

Jay Bojič Burgos, Urban Sedlar, Matevž Pustišek

No abstract is available for this record.

Nicolin Decker

No abstract is available for this record.

Jeremies Enmanuel Chinchay Camargo, Massiel Fiorella Parvina Huaman, Carmen Luz Cuba Cornejo, Cesar Augusto Cabrera Garcia

Digital electoral security has become fundamental to the development of reliable, integrated and available technological systems, driven by the growing demand for transparency and protection against threats. The purpose of this study is to analyze the impact of cryptographic protocols on the security of electoral processes, evaluating their effectiveness against traditional methods. For this purpose, a systematic review of the literature was carried out, considering 50 articles extracted from the Scopus database. The analysis focused on cryptographic techniques applied to blockchain-based environments, such as homomorphic encryption, zero-knowledge proofs and smart contracts, evaluating their contribution to design more secure, auditable and reliable voting systems. The results show that these protocols contribute to prevent recurring vulnerabilities, such as vote tampering, electoral fraud, impersonation and lack of validation, in addition to strengthening auditability and operational reliabilityFinally, the study concludes that the adoption and assessment of cryptographic protocols are essential to reduce risks in electronic voting, and promote more secure, transparent and efficient electoral processes.

Ralph Vince

No abstract is available for this record.

Tuan-Dung Tran, Khoi Le Quoc

No abstract is available for this record.

Md. Jueal Mia, M. Hadi Amini

Federated Learning (FL) is a decentralized learning method that enables collaborative model training while preserving data privacy. This makes FL a promising solution in various applications, particularly in cross-silo settings such as healthcare, finance, and transportation. However, FL remains highly vulnerable to adversarial threats, especially backdoor attacks, where malicious clients inject poisoned data to manipulate global model behavior. Existing outlier detection techniques often struggle to effectively isolate such adversarial updates, compromising model integrity. To address this challenge, we propose Backdoor Attack Resilient Technique for Federated Learning (BART-FL), a novel lightweight defense mechanism that enhances FL security through malicious client filtering. Our method integrates Principal Component Analysis (PCA) for dimensionality reduction with cosine similarity for measuring pairwise distances between model updates andK-means clustering for detecting potentially malicious clients. To reliably identify the benign cluster, we introduce a multi-metric statistical voting mechanism based on point-level mean, median absolute deviation (MAD), and cluster-level mean. This approach strengthens model resilience against adversarial manipulations by identifying and filtering malicious updates before aggregation, thereby preserving the integrity of the global model. Experimental evaluations conducted on the LISA traffic light dataset, CIFAR-10, and CIFAR-100 demonstrate the effectiveness of BART-FL in maintaining model performance across diverse FL settings. Additionally, we perform a comparative analysis against existing backdoor defense techniques, highlighting BART-FL’s ability to improve security while ensuring computational efficiency. Our results showcase the potential of BART-FL as a scalable and adversary-resilient defense mechanism for secure training in cross-silo FL applications.

Charlotte ; https://orcid.org/0000-0003-2027-5549 Hoffmann, Krzysztof Z ; https://orcid.org/0000-0002-9139-1654 Pietrzak

No abstract is available for this record.

Hongguo Zhang, Yun-Ming Sun, Kaiqi Zhang, Zhibo Guan · 6 authors

With the rapid expansion of digital asset trading, the contradiction between data sharing and privacy protection has increasingly become a significant challenge in the Internet environment. To address this issue, this paper proposes a secure multi-party computation scheme based on blockchain technology. Firstly, in response to the risk of data leakage in distributed storage scenarios, a threshold-based encryption algorithm is designed, utilizing a distributed key protection mechanism to effectively prevent single-point failures and data breaches. Secondly, a smart contract system is developed: the ERC721 contract is used to confirm the ownership of data assets, the ERC20 contract facilitates the transfer of usage rights, and the threshold decryption contract ensures secure multi-party computation and compliant incentive distribution. The collaboration of these three types of contracts enables comprehensive on-chain management of data assets, covering the entire process from ownership confirmation and circulation to compliant usage. In addition, this paper integrates non-interactive zero-knowledge proofs into the multi-party interaction process, allowing public verification of data consistency and computational validity on the blockchain. Finally, experiments are conducted to evaluate the impact of computation latency, communication overhead, and encryption parameters on system performance. The proposed scheme demonstrates significant performance improvements over mainstream SMPC protocols, with a 95.4 % reduction in key generation time and a 19.5 % reduction in ciphertext decryption time. Meanwhile, the scheme effectively resists various semi-malicious attacks, ensuring data security and privacy. • A t-out-of-N threshold ElGamal-based MPC scheme is proposed for secure computation in synchronous environments. • A blockchain smart contract framework manages data assets' lifecycle by combining ERC721/ERC20 and threshold decryption. • A method verifies on-chain data consistency and computation validity using non-interactive zero-knowledge proofs.

Zounkaraneni Ngoupayou Limbepe, Keke Gai, Jing Yu

Federated learning (FL) has emerged as an efficient machine learning (ML) method with crucial privacy protection features. It is adapted for training models in Internet of Things (IoT)-related domains, including smart healthcare systems (SHSs), where the introduction of IoT devices and technologies can arise various security and privacy concerns. However, as FL cannot solely address all privacy challenges, privacy-enhancing technologies (PETs) and blockchain are often integrated to enhance privacy protection in FL frameworks within SHSs. The critical questions remain regarding how these technologies are integrated with FL and how they contribute to enhancing privacy protection in SHSs. This survey addresses these questions by investigating the recent advancements on the combination of FL with PETs and blockchain for privacy protection in smart healthcare. First, this survey emphasizes the critical integration of PETs into the FL context. Second, to address the challenge of integrating blockchain into FL, it examines three main technical dimensions such as blockchain-enabled model storage, blockchain-enabled aggregation, and blockchain-enabled gradient upload within FL frameworks. This survey further explores how these technologies collectively ensure the integrity and confidentiality of healthcare data, highlighting their significance in building a trustworthy SHS that safeguards sensitive patient information.

P. K. Sinha, Nishant Kumar, Piyush Aggarwal

No abstract is available for this record.

Khoa Tan Vo, Minh Ngo, Thu Nguyen, Thu-Thuy Ta · 7 authors

Scalability remains a key challenge for layer 1 blockchains. ZK-Rollups, leveraging zero-knowledge proofs, offer a promising layer 2 solution by improving throughput and reducing costs while preserving security. However, the performance of ZK-Rollup still poses a major barrier to practical implementation. The proving circuits in popular applications like ERC-20 transactions are highly complex, often containing a large number of constraints, which directly impacts the computation time and resources required to generate zero-knowledge proofs. This study presents an empirical study on the impact of constraint optimization in Circom on the performance of ERC-20 ZK-Rollups using Groth16. Three optimization levels (–O0, –O1, –O2) are evaluated across transaction batches ranging from 4 to 128, with further exploration up to 512 for specific optimization levels to assess scalability. Results show a trade-off: –O2 reduces constraints by up to 73.2% but increases compilation time by 213.35% at batch size 128, while –O1 offers a more balanced approach suitable for development stages. Findings confirm that proof generation time is closely tied to constraint count and complexity. Based on these insights, this study introduces ZCLS (ZK-Circuit Lifecycle Strategy), a practical framework for selecting optimization flags aligned with development stages to enhance ZK-Rollup system efficiency.

Carmen Wabartha

The end-to-end verifiable e-voting system Ordinos [26] is primarily characterized by its tally-hiding property, which ensures that only the actual election result, e. g., the winner of the election, is revealed while the full tally consisting of the aggregated votes stays hidden. Ordinos is an abstract model that guarantees tally-hiding, verifiability and vote privacy if the underlying cryptographic primitives satisfy certain requirements. It uses a multi-party-computation protocol over an additively homomorphic encryption scheme and guarantees active security with zero-knowledge proofs. Ordinos has already been instantiated for several election systems using the Paillier [35] encryption scheme, which can be broken by Shor’s algorithm [41]. The aim of this thesis is to instantiate Ordinos post-quantum secure using a variant of Regev’s LWE-based cryptosystem [39], which is adapted to realize an actively secure threshold encryption scheme over an arbitrary plaintext space. Then a noise analysis of the arithmetic and logical components used in the MPC-protocol of the Paillier instantiation is conducted, and the components are slightly adapted to restrict the noise growth. Additionally, valid zero-knowledge proofs are provided and a concrete instantiation achieving a security level of 128 bits is shown.

Carmen Wabartha

The end-to-end verifiable e-voting system Ordinos [26] is primarily characterized by its tally-hiding property, which ensures that only the actual election result, e. g., the winner of the election, is revealed while the full tally consisting of the aggregated votes stays hidden. Ordinos is an abstract model that guarantees tally-hiding, verifiability and vote privacy if the underlying cryptographic primitives satisfy certain requirements. It uses a multi-party-computation protocol over an additively homomorphic encryption scheme and guarantees active security with zero-knowledge proofs. Ordinos has already been instantiated for several election systems using the Paillier [35] encryption scheme, which can be broken by Shor’s algorithm [41]. The aim of this thesis is to instantiate Ordinos post-quantum secure using a variant of Regev’s LWE-based cryptosystem [39], which is adapted to realize an actively secure threshold encryption scheme over an arbitrary plaintext space. Then a noise analysis of the arithmetic and logical components used in the MPC-protocol of the Paillier instantiation is conducted, and the components are slightly adapted to restrict the noise growth. Additionally, valid zero-knowledge proofs are provided and a concrete instantiation achieving a security level of 128 bits is shown.

Chen-Fan Chang, Ting‐Yu Chang, Chih-Chieh Chang, Te-Chuan Chiu · 6 authors

No abstract is available for this record.

Tumu Rajasekhar Babu

Federated learning represents a transformative approach in the realm of machine learning by enabling the training of models across decentralized devices while maintaining data privacy. Traditional centralized learning methods often compromise user privacy and data security by requiring the aggregation of data on a central server. In contrast, federated learning decentralizes the training process, allowing devices to collaboratively learn a shared model without exposing their private data. This paper explores the intricacies of federated learning, emphasizing its potential to enhance privacy and efficiency in AI systems. We delve into the technical architecture of federated learning, discussing key components such as data partitioning, model aggregation, and communication protocols. Furthermore, we address the challenges associated with federated learning, including data heterogeneity, communication overhead, and model convergence. Through comprehensive analysis and case studies, we demonstrate the efficacy of federated learning in various applications, from healthcare to finance. Our findings underscore the critical role of federated learning in safeguarding data privacy while optimizing the performance of machine learning models. As the demand for privacy preserving technologies continues to grow, federated learning emerges as a pivotal solution, paving the way for more secure and efficient AI systems.

Sorger, Tom

The growing importance of software supply chain security has revealed the critical need for securely sharing Software Bills of Materials (SBOMs). SBOMs enhance transparency by providing a detailed inventory of software components, but can inadvertently expose sensitive proprietary information and vulnerabilities when shared publicly. Addressing this challenge, this thesis explores the use of cryptographic techniques to achieve privacy-preserving and verifiable SBOM sharing. This thesis addresses this challenge by proposing zkSBOM (Zero-Knowledge Software Bill of Materials), a proof-of-concept system for privacy-preserving and verifiable SBOM sharing. It explores the system requirements and design for achieving secure yet transparent SBOM sharing, the effectiveness of various cryptographic techniques in safeguarding sensitive SBOM information, and the integration with real-world SBOMs. Through system design analysis and an experimental approach, this work provides solid insights into privacy-enhanced SBOM-sharing. The results demonstrate that the use of established cryptographic techniques is suitable to securely share SBOMs in real-world scenarios. We propose a centralised system enabling software vendors to upload their SBOMs and allowing verifiers to query for vulnerabilities. Additionally, we offer a local verifier system that allows verifiers to independently validate the proofs generated by the centralised system. The system leverages cryptographic techniques such as Merkle Trees, Sparse Merkle Trees, Merkle Patricia Tries, and Zero-Knowledge Sets. Using them, zkSBOM enables selective disclosure of SBOM information efficiently. The system ensures transparency through verifiable inclusion and non-inclusion proofs while safeguarding critical information. In a case study, we successfully ingest 16 out of 18 SBOMs and generate inclusion proofs for dependencies affected by a given vulnerability. This research contributes to advancing privacy-preserving SBOM sharing, paving the way for broader adoption in the software industry while strengthening the security of software supply chains.

Yurii Paslavskyi, Ihor Kroshnyi

An important cryptographic mechanism that guarantees confidentiality (the zero-disclosure property) and ensures that it is impossible to prove a false statement to the verifier is zero-disclosure proofs. A popular implementation of zero-disclosure proofs is short, noninteractive proofs that can be quickly verified and that do not require interaction between the parties after the initial setup. The main direction in the development of modern proof systems is interactive proof, which is built in two steps. The first is sending a confirmation of the polynomial of an interactive oracle proof and the second is creating correct oracles of the polynomial commitment scheme using well-defined cryptographic methods for evaluating polynomials. Verifying the use of the same coefficients in each linear combination requires checking both polynomial consistency and variable consistency. To construct general schemes of concise non-interactive zerodisclosure knowledge argument, an interactive oracle proof polynomial was proposed that models messages as polynomial oracles. All tests are proved using polynomial commitment schemes and then evaluated with zero knowledge at a point specified by the person verifying the information. The reliability and confidentiality of all tests are based on three main categories of interactive oracle proof polynomials, namely polynomial commitment schemes with conjunction, with inner product argument and with code theory. The protocols of concise noninteractive zero-disclosure knowledge arguments are implemented through high-level programs (compilers), which are converted into an intermediate representation, i.e. a scheme defined by a system of constraints. The compilers used are divided into domain-oriented languages, embedded domain-oriented languages, and zero-knowledge virtual machines. Specialized domain-oriented hardware description languages or programming languages offer an adapted syntax for efficiently expressing constraints in arithmetic schemes. Embedded domain-oriented languages are implemented as functions in general-purpose programming languages and are oriented to the overhead schemes inherited from the embedded language. Zero-knowledge virtual machines process the opcode of the fetch-decodeexecute cycle, replicating the computation trace for general programs and generating corresponding zeroknowledge proofs. They are compatible with existing high-level programming languages and can use the features of existing compilers. Compilers are evaluated for cross- or syntactic compatibility. In general, the biggest obstacle to using non-interactive proof libraries is the lack of documentation. Standardization can help developers compare important features across libraries and establish a more consistent performance baseline. Library documentation for these core features is implicit, and developers need to understand the underlying cryptographic techniques to choose an appropriate scheme. Standardization of compiler options is important, making it difficult to reuse existing tools.

George Teşeleanu

Abstract We present two simple zero-knowledge interactive proofs that can be instantiated with many of the standard decisional or computational hardness assumptions. Compared with traditional zero-knowledge proofs, in our protocols, the verifier starts first, by emitting a challenge, and then, the prover answers the challenge.

Istiaque Ahmed, Kentaroh Toyoda, Tadashi Nakano, Thi Hong Tran

Traditional digital identity systems struggle with centralization, vulnerability to manipulation, and a lack of transparency. In distributed identity, different cryptographic methods are used for issuing credentials, that create challenges during presentation. It suffer from a fundamental interoperability barrier with heterogeneous digital-signature schemes, forcing each verifier either to implement every scheme or to trust a central translation gateway. We propose a signature-agnostic verification framework that eliminates this barrier. The core idea is to commit a salted root hash of credential claims to a distributed ledger and ensure the authenticity using a smart contract. A zero-knowledge proof (zk-SNARK) is used to prove a selected claim set without revealing actual information. The verification reduces to a single hash-consistency check, and the verifier never touches issuer-specific signatures. A pleasant side effect is that the same verifiable presentation (VP) can be reused across verifiers and sessions, since trust derives from the on-chain anchor rather than transient signatures. This research will advance the identification ecosystem, enabling applications such as eKYC across finance, healthcare, and other sectors. We implement our method on Ethereum Virtual Machine (EVM) using Groth16, benchmark gas cost, proof size, and latency, and show its feasibility and computational efficiency. The privacy and security analysis confirms that the proposed solution is resistant to various attacks.