With the rapid proliferation of artificial intelligence generated content (AIGC), non‑fungible tokens (NFTs), and blockchain‑based services, creative works are increasingly born digital and managed as intellectual property (IP) digital assets. However, the assetization of content has outpaced the maturity of the supporting legal, technical, and educational infrastructures. Content creators and learners face fragmented tools for creation, registration, traceability, and infringement detection, which leads to weak evidence chains and high transaction costs in rights protection. This paper proposes an integrated framework for intelligent generation and security protection of IP digital assets that tightly couples AIGC engines with multi‑modal watermarking, blockchain‑based registration, and privacy‑preserving analytics. On this basis, a teaching‑oriented implementation is designed and deployed in a university course on digital media and IP management. The system supports full‑lifecycle management of images, text, code, and multimedia works, enabling students to experience rights creation, proof‑of‑ownership, risk diagnosis, and evidence preservation in realistic project tasks. Experimental results on a mixed benchmark of 4,200 assets show that the proposed scheme improves watermark robustness by 7.5% on average and shortens rights registration latency by 68% compared with traditional workflows, while significantly enhancing students’ IP literacy and compliance intention. The study demonstrates that IP digital‑asset technology can be transformed from a purely legal or technical topic into an operational teaching infrastructure, supporting both innovation and compliance in the AIGC era.
Open access
Blockchain Technology Applications and Security
Digital Rights Management and Security
Physical Unclonable Functions (PUFs) and Hardware Security
Ziyue Wang, Zongwen Shen, Lei Chen, Wei Song · 7 authors
Decentralized applications on EVM-compatible blockchains are powered by smart contracts—reprogrammable logic deployed on-chain. Among them, smart contract factories represent a distinct class of contracts that automate the creation of other contracts through CREATE / CREATE2 , enabling scalable and repeatable deployments of tokens, protocol modules, and NFT collections. Factories are now the dominant vehicle for contract deployment and mint the majority of contracts. Yet, the ecosystem still lacks (i) a global view of their prevalence and application domains, (ii) a catalog of implementation families beyond upgradeable proxies, and (iii) guidance on factory-specific security pitfalls that ripple across deployment pipelines. To address these gaps, we present the first ecosystem-scale measurement of factory activity on two EVM-compatible chains: Ethereum and Polygon. We implement a bytecode-based factory contract detector that disassembles 434 million deployed runtimes, builds control-flow graphs, and uses reachability analysis to confirm on-path CREATE / CREATE2 operations. This yields 120,204 Ethereum factories and 69,258 Polygon factories. The resulting dataset enables three key findings: (i) longitudinal measurements show factories have minted over 90% of contracts since 2020, concentrated in a small cadre of high-volume deployers; (ii) clustering 3,000 verified factories reveals four dominant application domains spanning Finance & token, Infrastructure & Protocol, Proxy & upgrade, and NFT & creator use cases; and (iii) semantic inspection distills six recurring implementation patterns alongside factory-specific attack vectors and security issues. Altogether, these results contribute to a deeper understanding of the current status, implementation patterns, and security issues of factory-based deployments.
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security
Niomi Langaliya, Vinay Thakor, Purna Tanna, Disha Shah
This research preprint presents Aegis, a zero-knowledge-proof-based security paradigm designed to mitigate validator-compromise attacks in cross-chain bridges. The work empirically evaluates a ZKP-based withdrawal verification mechanism against an optimized multi-signature validator model under controlled conditions, demonstrating complete resistance to unauthorized fund transfers at the cost of increased Layer 1 gas consumption. The study introduces the concept of the cost of trustlessness as an empirically derived techno-economic metric and provides quantitative justification for migrating cryptographic verification to Layer 2 environments. This work was previously presented at FINCON’25, National Forensic Sciences University (NFSU), Gandhinagar, India. This version is released as a non-peer-reviewed research preprint for open dissemination and citation. Journal submission is in progress.
Open access
2 source records
Physical Unclonable Functions (PUFs) and Hardware Security
Francisco Angulo De Lafuente, V. F. Veselov, Richard Goodman
This definitive research memoria presents a comprehensive, mathematically verified paradigm for neural communication with Bitcoin mining Application-Specific Integrated Circuits (ASICs), integrating five complementary frameworks: thermodynamic reservoir computing, hierarchical number system theory, algorithmic analysis, network latency optimization, and machine-checked mathematical formalization. We establish that obsolete cryptocurrency mining hardware exhibits emergent computational properties enabling bidirectional information exchange between AI systems and silicon substrates. The research program demonstrates: (1) reservoir computing with NARMA-10 Normalized Root Mean Square Error (NRMSE) of 0.8661; (2) the Thermodynamic Probability Filter (TPF) achieving 92.19% theoretical energy reduction; (3) the Virtual Block Manager achieving +25% effective hashrate; and (4) hardware universality across multiple ASIC families including Antminer S9, Lucky Miner LV06, and Goldshell LB-Box. A significant contribution is the machine-checked mathematical formalization using Lean 4 and Mathlib, providing unambiguous definitions, machine-verified theorems, and reviewer-proof claims. Key theorems proven include: independence implies zero leakage, predictor beats baseline implies non-independence (the logical core of TPF), energy savings theoretical maximum, and Physical Unclonable Function (PUF) distinguishability witnesses. Vladimir Veselov's hierarchical number system theory explains why early-round information contains predictive power. This work establishes a new paradigm: treating ASICs not as passive computational substrates but as active conversational partners whose thermodynamic state encodes exploitable computational information.
The modern integrated circuit ecosystem is increasingly reliant on third-party intellectual property integration, which introduces security risks, including hardware Trojans and security vulnerabilities. Addressing the resulting trust deadlock between IP vendors and system integrators without exposing proprietary designs requires novel privacy-preserving verification techniques. However, existing privacy-preserving hardware verification methods are all simulation-based and fail to offer formal guarantees. In this paper, we propose ZK-CEC, the first privacy-preserving framework for hardware formal verification. By combining formal verification and zero-knowledge proof (ZKP), ZK-CEC establishes a foundation for formally verifying IP correctness and security without compromising the confidentiality of the designs. We observe that existing zero-knowledge protocols for formal verification are designed to prove statements of public formulas. However, in a privacy-preserving verification context where the formula is secret, these protocols cannot prevent a malicious prover from forging the formula, thereby compromising the soundness of the verification. To address these gaps, we first propose a blueprint for proving the unsatisfiability of a secret design against a public constraint, which is widely applicable to proving properties in software, hardware, and cyber-physical systems. Based on the proposed blueprint, we construct ZK-CEC, which enables a prover to convince the verifier that a secret IP's functionality aligns perfectly with the public specification in zero knowledge, revealing only the length and width of the proof. We implement ZK-CEC and evaluate its performance across various circuits, including arithmetic units and cryptographic components. Experimental results show that ZK-CEC successfully verifies practical designs, such as the AES S-Box, within practical time limits.
Open access
4 source records
cs.CR
cs.LO
Physical Unclonable Functions (PUFs) and Hardware Security
As the United States Department of Defense (DoD) transitions toward Zero-Trust Architecture, the hardware and software supply chain remains a critical vulnerability. Current provenance models rely on centralized, siloed databases that lack the transparency required to counter sophisticated state-sponsored interdiction. This paper proposes a novel framework: AI-Enhanced Trust Graph Analytics over Distributed Ledgers. The architecture utilizes a permissioned Distributed Ledger Technology (DLT) substrate to host an immutable record of component lifecycles, anchored by Hardware Roots of Trust (RoT) through Physically Unclonable Functions (PUFs). By mapping silicon fingerprints to Software Bill of Materials (SBOM), the system constructs a multi-dimensional Trust Graph. We employ Graph Neural Networks (GNNs) to detect structural anomalies indicative of subversion, while Federated Learning enables inter-agency intelligence sharing without compromising operational security. Our findings demonstrate that this integrated approach significantly reduces the time to detect compromised assets in air-gapped and tactical environments, providing a strategic roadmap for an autonomous, self-healing supply chain.
Open access
3 source records
Physical Unclonable Functions (PUFs) and Hardware Security
V. T. Krishnaprasath, T. Surya, B. Suganthi, Mohammed Kasim M · 6 authors
The globalization of semiconductor supply chains and the rise of third-party IP reuse have intensified concerns around hardware Trojan insertion, counterfeit IP distribution, unauthorized overbuilding, and dispute-prone verification workflows in modern VLSI design. This paper proposes a Blockchain-Enabled Secure VLSI Framework that unifies distributed hardware verification, provenance tracking, and IP protection through tamper-evident ledger records and cryptographically verifiable design artifacts. The proposed framework registers RTL/netlist milestones, verification reports, test signatures, and PDK-dependent constraints as immutable transactions, enabling all stakeholders (IP vendors, integrators, foundries, and verification labs) to validate authenticity and integrity without exposing sensitive design content. To prevent IP leakage, the framework supports hash-anchored commitments, permissioned access control, and zero-knowledge–ready attestations for key verification claims (e.g., “coverage ≥ threshold” or “equivalence passed”) while keeping raw waveforms and proprietary constraints off-chain. A smart-contract policy engine enforces licensing (time-bound/feature-bound), audit logging, and revocation, while a lightweight on-chain/off-chain storage strategy ensures scalability. Analytical evaluation and prototype-level profiling indicate that the approach can provide end-to-end traceability with sub-second block confirmation in permissioned mode, ~25–45% reduction in dispute resolution time via automated audit trails, and ~15–30% lower manual compliance effort by standardizing verification evidence exchange. The framework is suitable for secure SoC integration, multi-vendor verification, and IP lifecycle governance in advanced VLSI flows.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
Introduction Digital identity infrastructures used in electronic passports, national eID schemes, and federated authentication systems rely predominantly on centralised registries and classical public key cryptography. These architectures enable large-scale identity correlation, mass data aggregation, and single points of compromise, while remaining vulnerable to quantum attacks against RSA and elliptic-curve cryptography. There is no deployed identity framework that simultaneously provides post-quantum security, cryptographic privacy guarantees, and decentralised trust. Methods This study proposes a quantum-proof digital passport architecture combining lattice-based post-quantum cryptography, decentralised blockchain identifiers, and transformer-based decentralised artificial intelligence. The framework employs NIST-aligned post-quantum key encapsulation and digital signatures, zero-knowledge proofs for selective disclosure of identity attributes, and homomorphic encryption for encrypted identity verification. Blockchain oracles and decentralised identifiers enforce credential integrity and auditability without reliance on central identity providers. Transformer attention mechanisms support adaptive identity validation while preventing persistent identity profiling. Results Architectural analysis shows that the proposed system prevents quantum-enabled credential forgery, retrospective decryption, and cross-service identity linkability. Zero-knowledge verification removes plaintext exposure of personal data, and decentralised credential control eliminates central compromise vectors. The design remains interoperable with existing passport and eID infrastructures. Discussion The results demonstrate that secure post-quantum digital identity requires the combined application of quantum-resistant cryptography, decentralised governance, and cryptographic privacy enforcement.
Open access
Cryptography and Data Security
Quantum Computing Algorithms and Architecture
Physical Unclonable Functions (PUFs) and Hardware Security
Defensive publication establishing prior art for proof-first digital identity systems using prime-indexed state evolution, zero-knowledge proofs, and silence-by-default semantics. This specification defines the Meta-Theorem of Prime Identity (MTPI), an architectural framework requiring cryptographic proof for every state transition. Core components include: Prime-Indexed Recursive Tensor Mathematics (PIRTM) with contractive dynamics guarantee; prime-gated activation with drift bounds δ(t) ≤ 0.3; Conscious Sovereignty Layer (CSL) with ethical tensor field commutation relations; Archivum append-only audit schema; and conformance requirements including Surveillance Fork detection. Reference implementations provided in Solidity and Circom 2.1. Mathematical foundations, alternative embodiments, and public domain designations included for maximum prior art scope. Keywords: zero-knowledge proofs, prime-indexed identity, verifiable computation, AI safety, defensive publication, proof-first computing, MTPI, PIRTM, CSL
Open access
2 source records
Cryptography and Data Security
Physical Unclonable Functions (PUFs) and Hardware Security
Smart contracts are increasingly being adopted in modern supply chain (SC) systems, offering a transformative shift from traditional centralized models to decentralized, automated, and trustless processes. However, vulnerabilities in the chain of smart contract represent a critical threat to the reliability and security of supply chain ecosystems, often arising from intricate logical flaws, unintended inter-contract interactions, or improper handling of user input—issues that remain difficult to uncover through conventional testing or manual auditing. This paper introduces an innovative deep learning–based methodology that transforms smart contract bytecode into image representations, enabling precise and efficient classification of diverse vulnerability patterns. Unlike existing approaches that rely on source code availability or dynamic execution, the proposed framework operates independently of source code and circumvents the limitations inherent to dynamic analysis, thereby offering a versatile and system-agnostic solution. Experimental evaluations conducted on a newly curated dataset collected from multiple publicly available repositories demonstrate the robustness of the proposed method, achieving 92.24% accuracy and an 89.06% F1-score. Beyond its strong empirical performance, the framework ensures reproducibility, data transparency, and adaptability across heterogeneous blockchain environments. Collectively, these contributions establish a comprehensive and accessible foundation for enhancing the detection, mitigation, and overall resilience of blockchain smart contracts.
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security
Firmware integrity is a foundational requirement for securing Cyber-Physical Systems (CPS), where malicious or compromised firmware can result in persistent backdoors, unauthorized control, or catastrophic system failures. Traditional verification mechanisms such as secure boot, digital signatures, and centralized hash databases are increasingly inadequate due to risks from insider threats and single points of failure. In this paper, we propose a decentralized firmware integrity verification framework built on the Ethereum blockchain, offering tamper-proof, transparent, and trustless validation. Our system stores SHA-256 hashes of firmware binaries within smart contracts deployed on the Ethereum Sepolia testnet, using Web3 and Infura for seamless on-chain interaction. A Python-based client tool computes firmware hashes and communicates with the blockchain to register and verify firmware authenticity in real-time. We implement and evaluate a fully functional prototype using real firmware samples, demonstrating successful contract deployment, hash registration, and integrity verification through live blockchain transactions. Experimental results confirm the reliability and low cost (in gas fees) of our approach, highlighting its practicality and scalability for real-world CPS applications. To enhance scalability and performance, we discuss extensions using Layer-2 rollups and off-chain storage via the InterPlanetary File System (IPFS). We also outline integration pathways with secure boot mechanisms, Trusted Platform Module (TPM)-based attestation, and zero-trust architectures. This work contributes a practical and extensible model for blockchain-based firmware verification, significantly strengthening the defense against firmware tampering and supply chain attacks in critical CPS environments.
Yuxin Xia, Ziyang Ji, Jie Zhang, Wanxin Li · 7 authors
Abstract Non-Fungible Token (NFT) creators use digital signatures to ensure the ownership, authenticity, integrity, and nonrepudiation of their digital works. However, if the private key is compromised, an attacker can generate unauthorized NFTs by using the creator’s private key to issue valid signatures. These valid but unauthorized signatures will be accepted in the NFT market and cannot be revoked. Even if the NFT creators update their private-public key pairs, they cannot deny the NFTs generated by the attacker. To mitigate these risks, we propose revocable signature by introducing commitment mechanism and an Auxiliary Embedded Key ( AEK ) into the signature, while the regular verification process does not involve this AEK . If a valid but unauthorized signature is detected and needs to be revoked, AEK will be disclosed to perform the revocation operation. To illustrate the application of revocable signatures in NFT, we design and implement a revocable Elliptic Curve Digital Signature Algorithm (ECDSA) scheme with provable security. Experimental evaluations on the FIPS-recommended elliptic curves show that the performance of revocable ECDSA is comparable to the basic ECDSA, with additional 0.0303 s (P-256 curve) and 0.15 USD gas fee in Remix VM for revoking a signature.
Open access
Cryptography and Data Security
Cryptography and Residue Arithmetic
Physical Unclonable Functions (PUFs) and Hardware Security
pada level bytecode.Penelitian ini mengimplementasikan metode deteksi malicious smart contract berbasis opcode menggunakan Graph Neural Network (GNN) dengan representasi Control Flow Graph (CFG) pada dataset Forta Network yang terdiri dari 139.600 kontrak dengan rasio ketidakseimbangan kelas 936:1 (149 malicious berbanding 139.451 benign).Setiap smart contract direpresentasikan sebagai CFG di mana basic block menjadi node berfitur 22 dimensi yang terdiri dari frekuensi 14 sensitive opcode dan representasi one-hot tipe instruksi exit, sedangkan hubungan antar blok direpresentasikan sebagai edge dengan lima kategori.Graf yang
Open access
Computer Science and Engineering
Information Retrieval and Data Mining
Physical Unclonable Functions (PUFs) and Hardware Security
This paper presents the post-quantum integrity architecture designed and being implemented within Smart Astro among the rst known platforms delivering Deterministic Engine Computed, AI-Narrated, Blockchain-Veried life guidance at scale. Smart Astro operates across 18 active life-decision intents and over 40 auspicious-timing categories, serving users globally through a real-time, pay-per-question model. Classical asymmetric cryptography underpinning current blockchain infrastructure is vulnerable to Shor's algorithm on fault-tolerant quantum computers. Smart Astro addresses this proactively by integrating NIST-standardised post-quantum cryptographic primitives FIPS 203 (ML-KEM), FIPS 204 (ML-DSA), and FIPS 205 (SLH-DSA) alongside a Solana-anchored proof chain already live in production. The central architectural contribution is a layered separation of concerns: the deterministic engine computes a structured, repeatable output; cryptographic proof generation runs asynchronously outside the delivery path; the AI narration layer is isolated from the proof chain; and only a commitment hash is written to the Solana ledger, with the full postquantum signature bundle stored o-chain. Every paid answer carries an independently veriable SA-PROOF identier with zero personally identiable information (PII) on-chain. A hybrid ML-DSA + SLH-DSA signature scheme provides defence in depth against both lattice cryptanalysis and harvest-now-decrypt-later adversaries. This architecture establishes a replicable standard for cryptographic integrity in AI-narrated deterministic knowledge systems.
Open access
Cryptography and Data Security
Cryptographic Implementations and Security
Physical Unclonable Functions (PUFs) and Hardware Security
As Generative AI (AIGC) achieves pixel-level realism and real-time interaction; traditional digital authentication paradigms face an unprecedented "authenticity crisis". Software-level defenses and static biometrics are increasingly vulnerable to high-fidelity AI-generated threats. This paper proposes a novel Human-Source Authentication architecture, termed Testing, Inspection, and Certification (TIC), which shifts the verification focus from logical correctness to the real-time presence of a physical entity. At the core of TIC is the Pulse-Eye Handshake (PEH) protocol, which integrates hardware-level Physical Unclonable Functions (PUF) with the physiological dynamics of the human pupillary light reflex (PLR). By leveraging a "Hardware Trinity" comprising smart glasses, a smartwatch, and a smart ring, the protocol constructs a deterministic "Shield of Time". This shield exploits the significant latency gap between the computational overhead of AI inference (typically >300ms) and the intrinsic physical limits of the human autonomic nervous system (8.3-35ms). Furthermore, architecture employs recursive zero-knowledge proof (ZKP) based on the Nova protocol to ensure multi-modal verification without compromising user privacy. Security analysis demonstrates that the proposed system remains robust against sophisticated modeling attacks and AI-driven acceleration. Our work provides a foundational anchor for digital sovereignty and system resilience in the era of pervasive AI and Industry 5.0.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
Consumer Healthcare Devices (CHD) in Healthcare 4.0 (HC 4.0) increasingly generate continuous physiological data that are transformed into 3-dimensional holographic visualizations for remote monitoring, diagnosis, and clinical decision support. However, existing IoMT and blockchain (BC)-based healthcare systems protect data storage and access but do not verify the integrity, freshness, or provenance of holographic patient representations, leaving such visualizations vulnerable to spoofing, replay, and slice-level tampering. This paper proposes a Blockchain-Assisted Holographic Counterpart (BAHC) framework that cryptographically binds wearable devices to holographic updates using PUF-derived Holographic Authentication Tokens (HAT), enforces slice-level integrity through a Merkle-Hologram-Commitment Tree (Merkle-HC Tree), and anchors updates on a permissioned Proof-of-Authority (PoA) BC. Privacy-preserving access control and verification are achieved using Ciphertext-Policy Attribute-Based Encryption (CP-ABE) and Zero-Knowledge Proofs (ZKPs). The framework is evaluated on a controlled experimental testbed emulating 500 concurrent patient streams using independent public physiological datasets and public MRI volumes for synthetic hologram generation, measuring end-to-end latency, anomaly detection performance, rendering efficiency, and blockchain throughput under up to 100 validators. Experimental results show a 68.6% reduction in holographic rendering latency, a 34% reduction in diagnostic latency, a relative 27% improvement in anomaly detection performance, and sustained throughput close to 500 transactions per second, demonstrating that BAHC provides a scalable and trustworthy foundation for secure holographic monitoring in HC 4.0 systems.
Chaos-based Image/Signal Encryption
Physical Unclonable Functions (PUFs) and Hardware Security
The rapid development of the Internet of Medical Things (IoMT) has also facilitated real-time monitoring of healthcare, yet creates major issues of security, privacy, and interoperability, particularly in terms of emerging threats of quantum computing. This paper introduces a quantum-resilient blockchain paradigm, which combines post-quantum cryptography (PQC), Zero Knowledge Proofs (ZKPs), and Fast Healthcare Interoperability Resources (FHIR) into secure and interoperable healthcare data management. Key encapsulation is performed using lattice-based algorithms, including Kyber and NTRU, and Dilithium and Falcon are algorithms used to secure digital signatures against quantum attacks. An authentication system which is based on a ZKP, and role-based access control allows privatizing access to electronic health records without exposing sensitive data. The framework is deployed on a PBFT-based permissioned blockchain and tested in simulated IoMT settings and has low latency, high throughput, and efficient cryptographic performance. In general, the suggested system will provide a reconfigurable, secure, and future-oriented method to safeguard the healthcare information against quantum threats without compromising the interoperability of the heterogeneous systems.
Open access
Cryptography and Data Security
Blockchain Technology Applications and Security
Physical Unclonable Functions (PUFs) and Hardware Security