Blockchain Papers

Morshed Mannan, Primavera De Filippi

No abstract is available for this record.

Kolja Sahm, George M. Giaglis

The nomenclature of Decentralized Autonomous Organizations (DAOs) implies a capability for autonomous operation that remains theoretically undefined and empirically unverified. This paper addresses this blind spot by reframing DAO analysis through a reductionist systems engineering lens, defining autonomy strictly as a system’s capacity to achieve goals under uncertainty without external intervention. We propose a novel measurement framework adapted from robotics standards (0–5 scale) and apply it to a random sample of N= 50 DAOs. The results reveal a stark disconnect between promise and reality: the ecosystem is currently capped at agency (Level 3), with the vast majority functioning merely as automated, human-dependent systems. Through an ordered logit analysis, we demonstrate that while architectural design choices, specifically regarding governance formalization and oracle integration, drive lower-level automation, the probabilistic reasoning required for high autonomy is statistically absent. We conclude that until the technical barriers to artificial intelligence integration are overcome, the ecosystem will remain “DAOs in Name Only,” failing to fulfill the autonomous promise of their title.

Morshed Mannan, Primavera De Filippi

Abstract This chapter reviews and contributes to the debate concerning the fiduciary duties of network participants of blockchain systems, with a focus on software developers and decentralized autonomous organization (DAO) members. After briefly introducing the concept of fiduciary duties in the UK and the US, the chapter surveys the early academic debates on the fiduciary status of core developers. It then turns to an analysis of the main case law in England and California relating to fiduciary duties in this space, before arguing that the imposition of implicit fiduciary duties could lead to unjust outcomes, deter participation in blockchain systems, and stifle innovation. Instead, the remainder of the chapter contends that pursuing co-regulatory efforts which are grounded in the principle of regulatory equivalence, such as the adoption of the COALA DAO Model Law, will secure the public policy objectives of imposing fiduciary duties, without sacrificing the distinctive features of blockchain networks.

А. М. Verchenkova

Секция 5. Логистика в современном бизнесе.

Naufal Ziyaadaturrahman

No abstract is available for this record.

ietje Smid-Woelders

The Prism Protocol is a privacy-native authentication and identity architecture in which a user can prove attributes or authentication state without directly revealing their identity to the server. It combines WebAuthn (W3C Level 3), Zero-Knowledge Proofs (Groth16 via circom/snarkjs), and NFC-based physical presence verification into a single coherent protocol stack. The core mechanism is a triangular key derivation model: biometric authentication (WebAuthn), a device-bound private key (FIDO2 Secure Enclave), and a time-limited wearable nonce (NFC ISO 14443 or BLE) jointly produce an ephemeral key. In v14, a working ZKP implementation is demonstrated: an age-threshold circuit proves that a user meets a criterion without the server ever receiving the attribute value. Verification is performed server-side via snarkjs.groth16.verify(). Within the demonstrated implementation flow, the server receives no name, no biometric data, no persistent identifier, and no direct attribute value. Sessions are designed to be mathematically unlinkable from the server perspective. A working proof-of-concept was demonstrated on 25 April 2026 at prismpass.globalsecurity.nu. The broader ecosystem (PrismPass, PrismID, PrismShield, PrismAdd, PrismChat, PrismAir, PrismGuard, PrismHash, PrismWipe) is documented in this Invention Disclosure. The protocol introduces no novel cryptographic primitives; its novelty lies in the specific architectural combination, orchestration model, and protocol-class definition addressing twelve authentication questions not simultaneously addressed by existing systems. Note: The post-quantum migration path (ML-KEM-768, ML-DSA-65) is documented as a formal architectural claim and forward-compatibility design decision. It describes the intended migration route, not a currently implemented feature. The working implementation uses ECDH, ECDSA, AES-256-GCM and Groth16. Author: I. Smid-Woelders, independent inventor, Zwolle, Netherlands. First documented: 25 April 2026. Contact: contact@globalsecurity.nu

Linda Handayani, Eri P. Wibowo, Avinanta Tarigan, Asep Juarna

No abstract is available for this record.

Meghna K. Bhatt, Mohammad Shabaz, Gyanendra Kumar

Digital Twin (DT) technology is elevating the next-generation intelligent transportation systems industry to new heights, as it enables real-time monitoring, predictive maintenance, and adaptive control of connected and autonomous vehicles. However, the use of GenAI and DTs in interconnected vehicular technology ecosystems introduces new attack vectors, particularly from quantum computing, which can easily break classical encryption systems. This paper introduces Reputation-based Proof-of-Stake (R-PoS), a hybrid consensus mechanism tailored for lattice-based PQC operations on vehicular edge devices. The core contribution is a lightweight hybrid consensus mechanism optimized for lattice-based PQC on edge devices, enabling secure and scalable synchronization between physical assets and their digital twins. Experimental results from a containerized IoT testbed using the Open Quantum Safe (OQS) library show that the proposed PQC-BC framework achieves an average throughput of 1178 transactions per second with latency of 0.78 second. These results affirm the framework's efficacy in securing future interconnected vehicular environments and establishing a trust foundation for sustainable quantum-resistant digital twin applications.

Adya Pratapchandran

No abstract is available for this record.

Odnala Srinivas, Mallu Shiva Rama Krishna, G. Bhavani, Pullela Gokul Krishna · 7 authors

The exponential growth of IoT devices in smart city infrastructures generates vast edge data, demanding secure, low latency, energy-efficient processing. Conventional cloud-centric models face bandwidth bottlenecks, latency overhead, and single-point vulnerabilities, necessitating decentralized management. This research introduces BQAREM: Blockchain-Secured Quantum Adaptive Resource Management for Edge Machine Learning, integrating blockchain security, quantum optimization, reinforcement learning. The framework employs timestamped identity verification, multi parameter trust assessment, and a weighted Proof-of-Stake consensus for secure coordination. Quantum adaptive scheduling and smart contracts ensure efficient, tamper-proof resource allocation, achieving superior latency, energy efficiency, SLA compliance. Comprehensive performance evaluation demonstrates that BQAREM significantly enhances reliability, scalability, intelligent resource orchestration across heterogeneous edge environments. Testing in various smart city scenarios including Smart Grid Control, Traffic Management, Healthcare Monitoring, Surveillance Systems, and Emergency Response demonstrates high accuracy (> 95%), reduced latency (< 50 ms), and efficiency improvements exceeding 80%, with balanced energy use. BQAREM uniquely unifies blockchain-backed trust like timestamped identity + weighted PoS, quantum-adaptive risk-sensitive RL, and multi-resource orchestration with a new Robust Performance Index (RPI) for secure, low-latency, energy-aware Edge-ML scheduling.

Steven Paul Nohr

<b>Maximal Extractable Value (MEV)</b> has evolved from a theoretical artifact of transparent transaction ordering into a dominant economic force shaping Proof-of-Stake (PoS) blockchain ecosystems. While early research framed MEV as an unavoidable but competitive phenomenon, recent infrastructure developments—particularly MEV relays, aggregators, and proposer-builder separation (PBS)—have enabled the consolidation of extractive power into coordinated intermediary groups. This paper introduces <b><i>MEV Aggregator Drift</i></b>, a structural phenomenon in which MEV extraction progressively centralizes into opaque, off-chain coordination clusters <b><i>(“collusion packs”)</i></b> that undermine validator neutrality, distort protocol incentives, and introduce cartel-like dynamics without explicit on-chain collusion. We analyze the economic drivers, execution mechanisms, and systemic risks of MEV collusion across PoS and DeFi systems, and argue that existing mitigations focus on efficiency while neglecting enforceable neutrality. Finally, we outline mitigation requirements centered on validator accountability, behavioral monitoring, and transaction ordering attestation.

Peyman Karimi, Gholamreza Askarzadeh Dareh, Alireza Rayati Shavazi, Seyed Yahya Abtahi

This study aimed to develop a conceptual model for pricing digital assets by integrating behavioral finance perspectives and identifying psychological and social factors influencing investors’ decision-making in decentralized markets. A qualitative grounded theory approach was adopted. The study involved 15 experts in digital currencies, blockchain, and behavioral finance selected through purposive sampling until theoretical saturation was achieved. Data were collected via semi-structured interviews and textual content analysis. Open, axial, and selective coding were applied to build the theoretical framework. Reliability was confirmed using quality control indices such as Krippendorff’s alpha, Holsti coefficient, Scott’s Pi, and Cohen’s Kappa, all indicating high inter-coder agreement. The resulting model captured multiple determinants of digital asset pricing. Causal factors included emotional and psychological behaviors (e.g., fear of missing out, fear and greed), the influence of news and media, and social association effects. Contextual factors encompassed uncertainty, ambiguity, and market volatility. Strategic factors such as market trust and credibility, investors’ knowledge and awareness, and reference points were identified. Core conditions included regulatory and legal environments, technological infrastructure, and macroeconomic conditions. Consequences involved enhanced market transparency, analysts’ and advisors’ influence, institutional and retail investor interactions, and the impact of past experiences on risk-taking. The proposed behavioral finance-driven model demonstrates that digital asset pricing extends beyond classical economic frameworks, heavily shaped by investor psychology and external information dynamics. The findings can guide investors toward more rational strategies and support policymakers in creating effective regulations and safer decentralized financial ecosystems.

João Pires da Cruz, Daniel Costa, Armando Teixeira, João B. Duarte · 6 authors

No abstract is available for this record.

Rujia Li, Mingfei Zhang, Xueqian Lu, Wenbo Xu · 6 authors

No abstract is available for this record.

Hideshi Itoh, Kimiyuki Morita

No abstract is available for this record.

Yuki YASUNO, Shusuke Chida, 永田光葉, Daiki Izumi · 5 authors

Recent advances in distributed system design have shifted from centralized client–server models to decentralized frameworks that enable broad inter-organizational collaboration. While Decentralized Autonomous Organizations (DAOs) leverage blockchain for governance and token-based transactions, existing platforms face two major limitations: the absence of decentralized authorization mechanisms and inadequate support for large-scale data management. This paper introduces Agentic DAO, a next-generation DAO architecture that integrates multi-agent authorization and scalable data governance into a blockchain-centric framework. The platform employs a Trust Scoring Agent using Graph Neural Networks (GNNs) to predict transactional reliability and a Data Management Agent to ensure consistency between blockchain and IPFS-based storage. Governance is reinforced through SoulBound Token (SBT)-based credentials to prevent Sybil attacks and enforce fair participation. A prototype implementation demonstrates the feasibility of trust-based access control and robust data synchronization. Experimental results confirm that Agentic DAO enhances transparency, scalability, and fairness compared to conventional DAO models, enabling secure and collaborative engagement in decentralized ecosystems.

Ming Sen Thong

No abstract is available for this record.

Kevin Werbach

Abstract As we look to the future, how might decentralized autonomous organizations (DAOs) evolve? And where, beyond corporate law, might we find guidance for the legal questions those evolved DAOs pose? DAOs are, and will increasingly become, instrumentalities of artificial intelligence (AI). DAOs are connected with AI in at least three ways: They are tools for decentralized governance of AI data and models; AI may be used to automate the management and operations of DAOs; and DAOs themselves may function as a form of AI. As such, DAOs inherit the major regulatory and ethical challenges that AI poses, most notably with regard to autonomy. Thus, to consider the future questions DAOs pose and how to address them, we must look to the raging debates over AI regulation, and connect them to the more established themes of corporate law.

Eduardo Miranda Ribera

Abstract Blockchain technology indubitably offers opportunities for the trading of carbon credits through the tokenization of Verified Carbon Credits (VCCs) via DAO (Decentralized Autonomous Organizations). These organizations aim to facilitate the trading of VCCs, improve market transparency, reduce transaction costs by eliminating intermediaries and facilitate market access for small entities interested in exploiting this opportunity. Thus, the purpose of this paper—in line with the content of the U nidroit Project on the legal nature of verified carbon credits—is to analyse the tokenization of VCCs through DAOs, given the development of new platforms created for this purpose. To carry out this analysis, it is necessary to study the concepts of blockchain technology, digital assets and DAO.

Winfred Ayanga, Róbert Magda

No abstract is available for this record.

Mariana Reis

This paper presents Zero-Knowledge Federated Learning Guard (ZK-FLGuard), a privacy-preserving and verifiable federated learning framework for real-time anomaly detection in Fifth-Generation Mobile Network (5G)-enabled Internet of Things (IoT) environments. Building on the integration of zero-knowledge proofs (zk-SNARK—Zero-Knowledge Succinct Non-interactive Argument of Knowledge) and blockchain-based access control, ZK-FLGuard ensures the integrity of model updates without exposing private data. Using real-world intrusion detection datasets (CICIDS2017—Canadian Institute for Cybersecurity Intrusion Detection System 2017, TON_IoT—Telecommunications Organisation of the National Security—IoT) and a synthetic adversarial dataset, our evaluation shows that ZK-FLGuard achieves up to 0.96 F1-score (harmonic mean of precision and recall), improves recall in low-frequency attack detection, and introduces less than 10% additional latency overhead compared to standard Federated Learning (FL). Compared with centralized Long Short-Term Memory (LSTM) and FL without Zero-Knowledge Proof (ZKP), ZK-FLGuard provides competitive accuracy while ensuring verifiable computation and strong privacy guarantees. We address the critical challenge of securing federated anomaly detection in 5G-enabled IoT systems against data leakage, model poisoning, and unauthorized access. While FL preserves privacy by keeping raw data local, it remains vulnerable to gradient leakage and adversarial manipulation. Our hypothesis is that combining zero-knowledge proofs and blockchain with FL can deliver a scalable, tamper-resistant, and privacy-preserving detection pipeline suitable for resource-constrained edge environments.

John Okyere

Financial exclusion remains acute in Sub-Saharan Africa, where more than 350 million adults lack access to formal financial services. A defining barrier is the absence of verifable identity: in countries such as Mozambique, Tanzania, and Niger, over half of adults without mobile money accounts cite missing documentation as the primary obstacle. Existing remedies either centralise sensitive personal data, creating systemic privacy and security risks, or demand document-issuing infrastructure that does not yet exist in many communities. This paper proposes ZKP-IDFS (Zero-Knowledge Proof Identity for Financial Services), a decentralised, privacy preserving digital identity framework that lets individuals prove identity-related predicates to financial institutions without disclosing the underlying personal attributes. ZKP-IDFS combines Groth16 zk-SNARKs for succinct on-chain proof verification, Pedersen commitments for attribute hiding, a W3C-compliant Verifi-able Credential layer, and a lightweight USSD/SMS proof-relay channel designed for feature-phone users in low-connectivity environments. We formalise the cryptographic model, specify the system architecture, and present a simulated performance evaluation across four representative network conditions. Results from a controlled simulation study show that end-to-end proof generation and relay complete in under 4.2 seconds on entry-level Android handsets at 3G speeds, with on-chain verication costs below 0.003 USD on an EVM-compatible layer-2 chain; these results require validation in eld deployments. We further demonstrate compliance with FATF risk-based KYC guidance and with emerging African data-protection legislation.

Subhasis Thakur, Martín Serrano

No abstract is available for this record.

Sachdeva Ks

Digital identity is critical, yet centralized providers create single points of failure&#x2014;breaches have exposed billions of records&#x2014;and quantum computing threatens the classical public-key cryptography (RSA/ECC) on which these systems rely. We present a system-level integration of blockchain, zero-knowledge proofs (ZKPs), and post-quantum cryptography (PQC) for privacy-preserving digital identity. A blockchain-based decentralized identifier (DID) system removes central databases; all signing and key-encapsulation operations use lattice-based PQC (CRYSTALS-Dilithium and Kyber); and selective disclosure is provided by Groth16 zk-SNARKs, with revocation via on-chain Merkle non-membership accumulators. We specify the full credential lifecycle&#x2014;issuance, two-phase authentication, and revocation&#x2014;with an explicit trust boundary separating the in-circuit Groth16 relation from the off-circuit issuer-signature check. We report a measured evaluation on a reference prototype: under liboqs 0.15.0, Dilithium-II signs/verifies in 0.19/0.06 ms and Kyber-512 encapsulates/decapsulates in 0.018/0.022 ms; a single-authentication Groth16 proof over the 21,715-constraint BN254 credential circuit takes <inline-formula> <tex-math notation="LaTeX">$\approx 981$ </tex-math></inline-formula> ms (snarkJS) and <inline-formula> <tex-math notation="LaTeX">$\approx 177$ </tex-math></inline-formula> ms (native rapidsnark) on byte-identical inputs, with <inline-formula> <tex-math notation="LaTeX">$\approx 40$ </tex-math></inline-formula> ms verification, a 723-byte proof, and <inline-formula> <tex-math notation="LaTeX">$\approx 243$ </tex-math></inline-formula>,000 gas for on-chain verification on a local EVM. A lifecycle harness with a passing revoked-credential negative test validates correctness. The signing and key-encapsulation layers are quantum-safe under current lattice assumptions; the Groth16 proof layer is classically secure only, and its post-quantum migration is identified as future work. End-to-end credential unforgeability is conditioned on an honest holder wallet performing the off-circuit signature check (Assumption 5). Every quantitative claim is labelled measured [M], simulated [S], assumption [A], or future work [F].