Blockchain Papers

Hyeonbum Lee, Seunghun Paik, Hyunjung Son, Jae Hong Seo

An inner product argument (IPA) is a cryptographic proof system that serves as a fundamental building block for various applications, such as zero knowledge proofs and verifiable computation. Bulletproofs (IEEE S&P 2018), a well-known IPA under the discrete logarithm (DL) assumption, features a short, logarithmically-sized proof, making it suitable for blockchain applications. However, its major drawback is the linear verifier cost (O(N)), which presents a significant bottleneck in settings like verifiable computation. To address this, recent advancements have successfully reduced the verification complexity to square-root order (O(√N)) under the same assumption (e.g., Asiacrypt 2022, IEEE TIFS). In thiswork, we propose Cougar, a novel IPAthat breaks this square-root barrier to achieve an unprecedented cubic-root verifier complexity (O(3√N)), while strictly maintaining the compact logarithmic proof size (O(logN)) characteristic of Bulletproofs. To achieve this, Cougar introduces a generalized two-tier commitment framework combined with adisjoint interpolationstrategy for efficient consistency checks. We implemented Cougar in Rust and performed a comprehensive benchmarking against Bulletproofs and Leopard (IEEE TIFS). Our evaluation demonstrates that while Cougar incurs a moderate increase in prover overhead, its verification time scales significantly better for large instances. Concretely, for a witness size ofN= 220, Cougar achieves a 50× verification speed-up over Bulletproofs and exhibits a superior asymptotic growth rate compared to existing sublinear IPAs.

Yuexin Kang, Jing Zeng, Qing Xia, Zhilin Wu · 5 authors

No abstract is available for this record.

Oleksandr Kuznetsov, Yulia Khavikova, Valerii Bushkov, Dmytro Shchytov · 5 authors

Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) have emerged as a critical technology for privacy-preserving computation and blockchain applications. However, systematic performance analysis of practical implementations remains limited, hindering informed technology adoption decisions. This study presents a comprehensive benchmarking analysis of the Groth16 protocol implementation using the widely-adopted Circom-snarkjs framework. We developed an automated benchmarking platform that systematically measures performance across seven representative circuit types with varying computational complexity (1-11 R1CS constraints). Our methodology ensures reproducible measurements through controlled experimental design with statistical validation. The platform captures detailed metrics for all three phases of the Groth16 protocol: witness generation, proof creation, and verification. Results from 35 independent measurements reveal several important findings. Witness generation demonstrates consistent performance across circuit types, averaging 57.6±12.1 milliseconds. Proof generation times range from 832 to 1,147 milliseconds, showing non-linear scaling with circuit complexity. Verification times remain relatively stable (741-884 milliseconds), confirming Groth16's theoretical constant-time verification advantage. All measurements achieved 100% success rate with complete proof validation. Notably, circuit structure significantly impacts performance beyond simple constraint counting. Comparison-based circuits achieve 13.22 constraints per second efficiency, substantially outperforming arithmetic circuits (1.02-4.36 constraints/second). This finding provides actionable guidance for circuit design optimization. The study contributes an open-source benchmarking framework for reproducible zk-SNARK research and provides empirical performance data for technology adoption decisions. Our findings support the practical deployment of Groth16 for applications requiring efficient zero-knowledge proofs while highlighting optimization opportunities for circuit designers.

Y.Y.N. Li

We introduce behavior-bound signatures (BBS), a signature framework in which each signature attests not only to signer authenticity but also to the satisfaction of a prescribed behavioral policy. Unlike traditional digital signatures—whose acceptance is determined by identity validity alone—BBS enforces compliance at the level of the verification predicate: a signature is accepted if and only if a zero-knowledge proof establishes that a residual function value δ(x)=∣ϕ(x)−τ∣\delta(x)=|\phi(x)-\tau|δ(x)=∣ϕ(x)−τ∣ lies below a threshold ε\varepsilonε. Thus, compliance safety is reduced to zero-knowledge soundness rather than to external monitoring or honest-majority assumptions. We formalize policy-soundness under chosen-message attacks (PS-CMA), extending EUF-CMA by requiring that no adversary can produce a valid signature for any message whose induced action violates the policy predicate. We prove that BBS achieves PS-CMA security under standard assumptions: binding of Pedersen commitments, collision resistance of Poseidon, and soundness of the underlying zero-knowledge proof system (e.g., Bulletproofs or PLONK). Our construction instantiates the policy predicate via a private structure function ϕ(x)\phi(x)ϕ(x) and enforces δ(x)<ε\delta(x)<\varepsilonδ(x)<ε through a zero-knowledge range constraint, while revealing no information about the private parameters. Sequential signatures compose into a hash-linked trajectory, enabling verifiable ordering and completeness of action sequences. We additionally define the Function Approximation Inversion Problem (FAIP) as a conjectured hardness property of the structure function, and emphasize that the security of BBS does not rely on this conjecture.

Rodica Doina Zmaranda, Attila-Imre Kovacs, Daniela Elena Popescu, Alexandrina Mirela Pater

Securing electronic health records (EHR) requires strong guarantees for confidentiality, integrity, access control, and auditability. Traditional centralized architectures rely on database-level protection and internal logging, which remain vulnerable to insider misuse and undetected data modification. This study proposes a practical hybrid architecture in which medical content is stored encrypted off-chain, while blockchain is used selectively as a governance and evidence layer. An Ethereum-based prototype was designed and implemented to support integrity anchoring of medical documents, patient-controlled consent management, and immutable audit trails for critical actions. In the implemented solution, the actual medical content is not stored on-chain. Instead, the blockchain stores only document-related metadata, cryptographic hashes, document references, and access-control information, while the sensitive medical data remains encrypted and stored off-chain. This design supports GDPR-oriented data minimization, since the immutable blockchain layer does not contain raw medical records or directly identifiable medical content. The prototype separates confidentiality from blockchain immutability. Medical document confidentiality is handled at the application and off-chain storage level, while the blockchain is used for integrity verification, consent management, and auditability. Encryption keys are not stored on-chain, which prevents the blockchain layer from becoming a repository of sensitive or directly exploitable medical information. Security mechanisms are integrated directly into application flows, including hash-based tamper detection and on-chain verification of access rights. The prototype is evaluated through realistic operational scenarios, analyzing security properties, performance, and transaction cost implications. Results show that, relative to a DB-only baseline, the hybrid approach provides structurally stronger support for integrity verification, traceability, and accountability without exposing sensitive medical data on-chain. The study also highlights practical limitations related to latency and costs in public blockchain environments, supporting a selective on-chain design focused on high-value operations.

Fiza Siyal, Antonella Guzzo, Fahed Alkhabbas, D. Saccà · 5 authors

We propose a novel blockchain-based traceability system that uniquely combines Physical Unclonable Functions (PUFs) and Non-Fungible Tokens (NFTs) to establish secure, tamper-evident, and verifiable digital identities for physical products. Unlike conventional approaches that rely solely on serial numbers or barcodes, our system uses embedded PUFs to generate a physically unclonable ID for each item, ensuring hardware-level authenticity. This PUF ID is cryptographically linked to an NFT minted on a public blockchain, encapsulating metadata such as product origin, manufacturing details, and certification status. Associating NFTs and certifications with PUF-tagged products not only provides transparent provenance but also enables decentralised validation of compliance and ethical standards. This methodology is distinct in its integration of immutable physical identity with blockchain-based digital certification, offering a robust solution for enhancing transparency, combating counterfeiting, and fostering trust across global supply chains. Furthermore, employing Edge and emerging 6G networks, our framework can execute PUF challenge–response and preliminary NFT minting directly at edge nodes. This establishes a real-time, low-latency architecture that reduces network congestion and gas costs for secure and sustainable supply chains.

Benoît Prieur

No abstract is available for this record.

Elizaveta Pertseva, Valentin Robert, Clark Barrett, James Parker

Efforts to verify Zero-Knowledge Proof circuit encodings have highlighted the challenge of proving the correctness of quantifier-free statements that make use of both bitvector and finite field operations. Existing verification workflows are either manual or rely on SMT solvers, which scale poorly on some classes of problems for reasons that include difficulties with conversion operators and challenges reasoning about inequalities. To address these limitations, we present a novel Lean tactic BitModEq that leverages range lemmas and case analysis to produce verified translations from finite fields to bitvectors. Our approach, combined with bit-blasting, outperforms state-of-the-art SMT solvers, solving 19% more ZKP arithmetization benchmarks.

Priya Saxena, Shyam Jaiswal, Vaishnavi Mishra, A. Syed Ismail

No abstract is available for this record.

Chengsheng Yuan, Lvyang Cao, X F Li, Zhili Zhou · 6 authors

No abstract is available for this record.

Priya Patel, Nitesh Sureja

Ensuring transparency, security, and privacy in agricultural food supply chains is critical for maintaining consumer trust, regulatory compliance, and data integrity. Traditional centralized traceability systems suffer from several limitations, including data tampering risks, single-point failures, and potential privacy leakage. To address these challenges, this research proposes a privacy-preserving blockchain-based traceability framework that integrates the InterPlanetary File System (IPFS) with Zero-Knowledge Proofs (ZKPs). The framework leverages the Ethereum blockchain for immutable record-keeping, while zk-SNARK-based proofs enable compliance verification without revealing sensitive underlying data. A prototype was implemented using Solidity smart contracts and Python-based zk-SNARK circuits. Experimental evaluation across varying record sizes, from 50 to 200, demonstrates high security and efficiency, achieving 100% success in detecting simulated tampering attempts. Performance metrics indicate a highly scalable system with an average end-to-end latency of approximately 0.33 seconds, rapid proof generation times of approximately 0.0002 seconds, and near-constant verification times averaging 0.027 seconds. Furthermore, the system maintains a consistent simulated transaction cost of 20.40$ per proof, regardless of the total records processed. Overall, the proposed approach provides a robust, scalable, and computationally efficient solution for modern agri- food supply chains, successfully balancing data confidentiality with rigorous cryptographic integrity.

nithin nagineni

Zero-Knowledge Proofs (ZKPs) have emerged as a transformative cryptographic primitive enabling one party to prove the validity of a statement without revealing any underlying information. This property has made ZKPs a cornerstone in privacypreserving systems, particularly in blockchain, authentication protocols, and secure distributed computing. Despite rapid advancements in ZKP frameworks such as zk-SNARKs and zk-STARKs, the testing and validation of these systems remain a critical challenge. The complexity of arithmetic circuits, the probabilistic nature of proofs, and the potential for subtle vulnerabilities necessitate robust testing methodologies. This paper presents a comprehensive review of testing techniques for Zero-Knowledge Proof systems. It begins by outlining the fundamental properties of ZKPs, including completeness, soundness, and zero-knowledge, which form the basis for testing correctness and security. The study then explores existing literature on testing approaches, including formal verification, fuzz testing, constraint validation, and symbolic execution. Recent research highlights that vulnerabilities such as underconstrained circuits account for a significant portion of ZKP system failures, emphasizing the need for systematic testing strategies. Furthermore, this review categorizes testing techniques into functional, security, and performance testing, providing a structured understanding of their roles in ZKP validation. A comparative analysis of existing methods is also presented to evaluate their effectiveness, scalability, and limitations. The discussion identifies gaps in current research, particularly in automated testing frameworks and standardized benchmarking. The paper concludes by emphasizing the importance of integrating advanced testing methodologies into ZKP development pipelines to ensure reliability, scalability, and security. Future research directions include AI-driven testing, hybrid verification models, and improved tooling for circuit validation. This review aims to serve as a foundational reference for researchers and practitioners working on secure and efficient ZKP systems.

Hyunhum Cho, Ik Rae Jeong

The thriving Non-Fungible Token(NFT) market, despite its innovative redefinition of digital ownership, faces malicious attacks and challenges, notably from widespread wash trading. In this paper, we examine the underexplored relationship between NFT rarity and wash trading.We present a novel approach to NFT market dynamics, by establishing the first comprehensive formal framework for NFT trait systems, including essential definitions, a robust taxonomy, precise rarity calculation, and verifiable properties. Building upon this, we conduct an empirical analysis of NFT rarity and wash trading across 30 collections including 336,133 NFTs, 764,679 transactions, total volume of 14,394,949 in Ethereum. Our findings reveal the strong inverse correlation between a collection’s price-rarity coefficient and its wash trading volume, showing that the top 5 collections with the lowest price-rarity coefficients are overwhelmingly dominated by wash trading, averaging 89.29% of their total volume, in contrast to the vast majority of other collections which exhibited negligible volumes, consistently below 2%. Case studies further highlight the power of this price-rarity analysis as a novel anomaly detection tool: it exposed wash trading-induced distortions in CryptoPunks by detecting an outlier previously undetectable by existing graph-based approaches. We also demonstrate Rektguy’s remarkable resilience—absorbing 20.04% wash volume possibly due to strong rarity-price correlation. Our findings establish rarity as an intrinsic resilience factor against manipulation, fundamentally reshaping approaches to NFT market analysis and robust anomaly detection.

Joel Poncha Lemayian

Blockchain technology enables tamper-resistant and transparent data management, but it continues to face pressing challenges related to security and performance. Existing blockchain applications predominantly rely on software-based implementations, which are susceptible to side-channel analysis (SCA) attacks and constrained by the limited efficiency of general-purpose processors. This thesis addresses these challenges by leveraging Field-Programmable Gate Array (FPGA) technology to develop hardware-based solutions that strengthen cryptographic security and accelerate blockchain execution. Three major hardware contributions are presented: an Ethereum hardware wallet resistant to SCA, a hybrid Ethereum–Bitcoin hardware wallet supporting both Hierarchical Deterministic (HD) and Non-Deterministic (ND) modes, and a hardware-accelerated Ethereum Virtual Machine (EVM). The first contribution, EthVault, introduces the first complete hardware architecture of an Ethereum HD cold wallet and its FPGA implementation. EthVault integrates a side-channel resistant elliptic curve cryptography (ECC) design, the first hardware realization of the child key derivation (CKD) function, and resource-conscious implementations of key cryptographic algorithms, including ECDSA, HMAC-SHA-512, PBKDF2, SECP256K1, elliptic curve point operations, and the Ethereum checksum algorithm, resulting in a secure, compact wallet. The second contribution, HardVault, presents the first FPGA-based hybrid Ethereum–Bitcoin cold wallet architecture. Supporting both HD and ND key generation methods, HardVault improves resource efficiency by reusing cryptographic primitives common to Ethereum and Bitcoin, including RIPEMD-160, CKD, and SHA-256. This reuse minimizes hardware overhead, enabling a lightweight and energy-efficient solution. A detailed power–performance evaluation further demonstrates HardVault’s superior efficiency, with measurable improvements over commercial wallets such as Trezor One. The third contribution, EVMx, proposes a single-core FPGA-based EVM that offloads smart contract execution from full and archival nodes to a dedicated hardware accelerator. EVMx preserves full compatibility with the EVM’s stack-based semantics while introducing performance optimizations such as lightweight pipelining, simplified opcode decoding, dynamic corner-case handling, and selective parallelism. Experimental results show significant speedups for both individual opcodes and complete smart contract execution compared to CPU-based and prior FPGA designs. Furthermore, integration strategies are discussed to enable scalable adoption of EVMx within existing Ethereum clients. Overall, this thesis demonstrates that FPGA-based designs can substantially strengthen blockchain ecosystems by enhancing both security (EthVault and HardVault) and computational performance (EVMx), thereby paving the way for more secure, efficient, and practical blockchain deployments.

Chibuzor Udokwu, Seyed Amid Moeinzadeh Mirhosseini, Stefan Craß

Smart contracts are deployed and represented as bytecodes in blockchain networks, and these bytecodes are machine-readable codes. Only a small number of deployed smart contracts have their verified human-readable code publicly accessible to blockchain users. To improve the understandability of deployed smart contracts, we explored rule-based classification of smart contracts using iterative integration of fingerprints of relevant function interfaces and keywords. Our classification system included categories for standard contracts such as ERC20, ERC721, and ERC1155, and non-standard contracts like FinDApps, cross-chain, governance, and proxy. To do this, we first identified the core function fingerprints for all ERC token contracts. We then used an adapted header extractor tool to verify that these fingerprints occurred in all of the implemented functions within the bytecode. For the non-standard contracts, we took an iterative approach, identifying contract interfaces and relevant fingerprints for each specific category. To classify these contracts, we created a rule that required at least two occurrences of a relevant fingerprint keyword or interface. This rule was stricter for standard contracts: the 100% occurrence requirement ensures that we only identify compliant token contracts. For non-standard contracts, we required a minimum of two relevant fingerprint occurrences to prevent hash collisions and the unintentional use of keywords. After developing the classifier, we evaluated its performance on sample datasets. The classifier performed very well, achieving an F1 score of over 99% for standard contracts and a solid 93% for non-standard contracts. We also conducted a risk analysis to identify potential vulnerabilities that could reduce the classifier’s performance, including hash collisions, an incomplete rule set, manual verification bottlenecks, outdated data, and semantic misdirection or obfuscation of smart contract functions. To address these risks, we proposed several solutions: continuous monitoring, continuous data crawling, and extended rule refinement. The classifier’s modular design allows for these manual updates to be easily integrated. While semantic-based risks cannot be completely eliminated, symbolic execution can be used to verify the expected behavior of ERC token contract functions with a given set of inputs to identify malicious contracts. Lastly, we applied the classifier on contracts deployed Ethereum main network.

Rohit Razdan, Manisha J. Nene

Advancements in quantum processing technology threaten the core security mechanisms that protect contemporary distributed ledger platforms. Hyperledger Fabric, an enterprise- focused, permissioned ledger developed under the Linux Foundation’s open-source umbrella, caters to organizational priorities including data seclusion, expansion capabilities, and regulated user involvement. In contrast to decentralized public networks such as Bitcoin and Ethereum, Fabric incorporates verified entities, flexible validation protocols, and streamlined verification routines. Despite these strengths, its dependence on the Elliptic Curve Digital Signature Algorithm (ECDSA) exposes it to vulnerabilities from Shor’s computational method, which efficiently reconstructs confidential keys from exposed counterparts, thereby jeopardizing transaction validity, genuineness, and irrefutability. This study advocates for the incorporation of quantum-secure cryptographic techniques (PQC), particularly the CRYSTALS-Dilithium authentication protocol, into Hyperledger Fabric employing a merged authentication paradigm that fuses ECDSA with Dilithium. This blended strategy yields stratified defenses, comparable to redundant safety systems in vehicles, delivering endurance to quantum incursions while preserving synergy with established infrastructures. Initial testing demonstrates negligible impacts on operational efficiency coupled with notable bolstering of protective measures, facilitating the evolution of fortified, quantum-immune commercial ledgers that sustain enduring credibility and informational steadfastness. Keywords—Hyperledger Fabric, Permissioned Ledger, Quantum-Safe Cryptography, CRYSTALS-Dilithium, ECDSA, Quantum Safeguard, Ledger Steadfastness

Gazi Maliha Raisa Noor, Md Ashikul Islam, Saha Reno, S. Mahin

Managing intellectual property (IP) in the digital age presents significant challenges, including unauthorized duplication, unclear ownership, and insufficient verification mechanisms. This paper proposes a blockchain-based framework that integrates Hyperledger Fabric, Interplanetary File System (IPFS), and Non-Fungible Tokens (NFTs) to ensure secure, transparent, and tamper-proof IP management. Hyperledger Fabric serves as the permissioned blockchain platform, using the RAFT (Replicated And Fault-Tolerant) consensus protocol to achieve fast, fault-tolerant agreement with low latency and moderate resource consumption. IP assets are stored off-chain using IPFS, with their metadata encapsulated in NFTs for unique identification, traceability, and automated licensing via smart contracts. The system enables decentralized IP registration, verification, and transfer while preserving content integrity. Performance analysis shows that RAFT consistently outperforms PoW, PoS, and Clique in throughput, latency, and CPU usage, making it well-suited for high-performance enterprise applications. A cost breakdown also confirms the system's affordability and scalability. Finally, command-line validation demonstrates correct ledger operations and smart contract functionality. The proposed solution offers a practical and efficient alternative to traditional IP systems, with future improvements targeting enhanced access control and support for large-scale IP ecosystems.

Chibuzor Udokwu, Stefan Craß

Digital product passports outline information about a product’s lifecycle, circularity, and sustainability-related data. Sustainability data contains claims about carbon footprint, recycled material composition, ethical sourcing of production materials, etc. Also, upcoming regulatory directives require companies to disclose this type of information. However, current sustainability reporting practices face challenges, such as greenwashing, where companies make incorrect claims that are difficult to verify. There is also a challenge of disclosing sensitive production information when other stakeholders, such as consumers or other economic operators, wish to verify sustainability claims independently. Zero-knowledge proofs (ZKPs) provide a cryptographic system for verifying statements without revealing sensitive information. The goal of this research paper is to explore ZKP cryptography, trust models, and implementation concepts for extending DPP capability in privacy-aware reporting and verification of sustainability claims in products. To achieve this goal, first, formal representations of sustainability claims are provided. Then, a data matrix and trust model for generating proofs are developed. An interaction sequence is provided to show different components for various proof generation and verification scenarios for sustainability claims. Lastly, the paper provides a circuit template for the proof generation of an example claim and a credential structure for their input data validation. The proposed approach is assessed using a scenario-based evaluation to check the performance metrics for data credential verification and proof generation for verifying material composition in a product.

Dhanush K, Tamilvelan S, Hari L, R. Roopa Chandrika

The growing adoption of lightweight, scalable, and resistant to tampering security mechanisms in the face of broad use of Internet-of-Things (IoT) and edge computing devices requires such mechanisms to be not based on centralized trust or bulky cryptography. The promising answer to this is the concept of Physical Unclonable Functions (PUFs) which relies on naturally existing manufacturing differences to produce device-specific, unclonable responses. Nevertheless, existing PUF-based authentication systems have significant flaws, such as centralized Challenge-Response Pair (CRP) storage vulnerable to attacks, vulnerability to machine learning, and no support of secure data recovery and sharing in distributed settings. This paper suggests a distributed authentication and recoverable data sharing framework that reduces these drawbacks, PUF-as-a-Service (PUFaaS). PUFaaS presents a multi-dimensional space of CRP, spreading the domain of challenges with respect to various operational parameters to maximize security against modeling attacks. Helper data of fuzzy extractors are secured with Shamir's secret sharing over distributed nodes and without having single points of weakness. A mechanism based on fuzzy vaults provides recoverable data binding, whereby encryption keys or sensitive data can be re-assembled successfully on successful verification of stable PUF responses. Authentication is carried out by way of lightweight commitment protocol, message authentication protocol and optional zero-knowledge proof guarantees privacy. Experimental analysis shows that PUFaaS can be evaluated as having low false acceptance and rejection, high modeling attack resistance, and scale efficiently (appropriate to large-scale IoT and cloud-edge). PUFaaS will offer an effective, privacy-resilient, and scalable solution to distributed authentication and secure information exchange in a non-trusted environment by converting PUFs into a service-oriented architecture.

Ghassan Samara, Ibrahim Obeidat, Mais Haj Qasem, Raed Alazaidah · 9 authors

Vehicular networks must authenticate high-rate safety messages under tight latency while preserving privacy and remaining secure against post-quantum adversaries. We present$P Q$-Rate, a post-quantum, privacy-preserving, rate-limited credential system for C-V2X. PQ-Rate replaces per-message signatures with a one-round-trip (1-RTT) KEM handshake to derive an AEAD session key, keeping the fast path lightweight. Vehicles obtain unlinkable Rate-Limited Anonymous Tokens (RLATs) from edge issuers (RSU/MEC) via a threshold VOPRF; each token is spent once using a zero-knowledge proof that binds a unique nullifier, enforcing per-epoch budgets without revealing identity. Revocation scales via compact, signed Bloom-filter digests broadcast by RSUs, with optional online disambiguation to handle rare false positives, and accountability is provided by threshold opening of verifiably encrypted token metadata. We prototype PQ-Rate in NS-3 with SUMO-driven mobility and compare against pseudonym-based PKI and verifier-local-revocation group signatures. Metrics include 1-RTT authentication latency, beacon delivery ratio (PDR), channel busy ratio (CBR), verifier throughput, revocation-wire overhead, and realized Sybil capacity. Results show that PQ-Rate maintains sub- 20 ms session setup, improves PDR under high density by reducing airtime overhead, increases verifier throughput via batching and inexpensive decapsulation, and bounds attacker identities to the product of enrolled hardware modules and budget. Revocation digests remain small (on the order of 9-12 KB for thousands of inserts at$10^{-3}-10^{-4}$false-positive targets), supporting frequent broadcast without inflating CBR. PQ-Rate demonstrates that post-quantum security, strong privacy, Sybil resistance, and rapid revocation can be achieved simultaneously within V2X timing constraints.

Dimitrios Kasimatis, Ilias Politis, Nikolaos Pitropakis, Pavlos Papadopoulos · 5 authors

The rapid proliferation of Internet of Things (IoT) devices across various industries, including healthcare, smart cities, and industrial automation, has introduced significant security, authenticity, and traceability challenges within increasingly complex supply chains. Although existing approaches have utilised blockchain-based digital identity solutions to address some of these concerns, persistent issues of counterfeit products and inadequate lifecycle transparency highlight the need for more robust, hardware-anchored identification mechanisms. Our work presents a novel architecture that integrates Physically Unclonable Functions (PUFs) and blockchain-based Soulbound Tokens (SBTs) to establish secure and verifiable digital identities directly tied to the physical hardware of IoT devices. By employing cryptographic tools such as fuzzy extractors, Merkle trees, and zero-knowledge proofs, the proposed architecture ensures accurate lifecycle tracking through key operational stages, including manufacturing, procurement, provisioning, maintenance, and eventual disposal or recycling. Performance evaluations conducted on the Ethereum Sepolia testnet demonstrate reasonable computational overhead in terms of gas usage and transaction confirmation times. The findings reveal that this approach aligns with NIST Special Publication 800-161 guidelines, as well as emerging regulatory standards, notably the European Union’s Digital Product Passport initiative, and has significant implications for enhancing transparency, sustainability, and security across global IoT supply chains.

Quazi Mamun, Megumi Saito, Jiang Liu, Zhenni Pan · 5 authors

In 5G/6G networks, Device-to-Device (D2D) Salvage Transmission (ST) ensures communication continuity when Unreachable User Equipment (X) loses access to the base station. However, securing authentication between X and Salvage User Equipment (S) while maintaining privacy presents a challenge. Traditional authentication methods depend on key exchanges or centralised servers, heightening vulnerability to impersonation and replay attacks. This paper proposes a Zero-Knowledge Proof (ZKP)-based authentication protocol that enables lightweight, privacy-preserving authentication without disclosing private credentials. The approach utilises modular exponentiation and cryptographic hashing, allowing X to demonstrate its legitimacy without revealing its private key. Simulation results indicate that the proposed method achieves low authentication latency ( 1–10 ms), minimal communication overhead ( 80 bytes per session), and high scalability under heavy authentication loads. The scheme provides resistance against man-in-the-middle (MITM), impersonation, and replay attacks, making it highly secure for real-time applications.

Yunbo Yang, Yu Cheng, Junkai Liang, Kailun Wang · 14 authors

Zero-knowledge Succinct Non-interactive Argument of Knowledge (zkSNARK) is a powerful cryptographic primitive that enables a prover to convince a verifier that something is true without leaking the private witness. Current zkSNARKs face significant computational costs in generating proofs, which restricts their use in areas like private payments, confidential smart contracts, and anonymous credentials. Private delegation offers a practical solution by outsourcing the heavy computation to powerful external workers without leaking any private information. In this work, we propose HyperSiniel, an efficient private delegation framework for general zkSNARKs that achieves a new feature called guaranteed output delivery (GOD). HyperSiniel is designed to be compatible with any universal zkSNARKs constructed from a polynomial interactive oracle proof (PIOP) and a polynomial commitment scheme (PCS). It enables a computationally limited delegator to outsource proof generation to several workers in a fully non-interactive and privacy-preserving manner. Compared to the most state-of-the-art frameworks (e.g., Siniel [NDSS'25]), HyperSiniel ensures that the delegator always receives a correct proof, regardless of malicious worker behavior. We implement HyperSiniel and compare the performance with Siniel across varying bandwidths and circuit sizes. Under low-bandwidth conditions (10MBps), HyperSiniel incurs only an additional 25% overhead compared with Siniel, while the total running time of HyperSiniel is almost identical to Siniel under high-bandwidth settings (1000MBps). These results show that the strong robustness guarantee of GOD in HyperSiniel comes almost for free, making it a practical and secure solution for real-world zkSNARK delegation.

Chechelnitsky, Igor

This work introduces the Adversarial Cost Model (ACM v1.0), a formal security framework unifying computational, economic, and physical attack costs in a single rational adversary model. Unlike traditional security models based purely on computational hardness, ACM evaluates real-world feasibility of attacks under post-quantum cryptography, behavioral authentication, zero-knowledge proof systems, and decentralized governance. The model formalizes adversarial actions through total cost functions combining time complexity, hardware requirements, capital liquidity, and physical laboratory constraints. Multiple critical attack classes are analyzed, including hybrid side-channel + Grover attacks, GAN-based behavioral cloning, flash-loan Sybil governance attacks, post-quantum brute-force exhaustion, and zero-knowledge proof forgery. The results demonstrate that many real-world system failures arise not from cryptographic weakness, but from mispriced economic atomicity and cost-free identity or governance acquisition. ACM provides a rationality threshold theorem formalizing when attacks become economically and physically irrational. The model directly informs secure system architecture design by enforcing multi-layer cost escalation across cryptographic, physical, behavioral, and governance layers. This work is intended for cryptography, blockchain security, adversarial machine learning, economic attack modeling, and post-quantum system design.