Oscar M. Bedoya, Jeferson Arango‐López, Jorge Hochstetter
The management of intellectual property (IP) agreements in universities continues to rely on static legal documents that are signed, archived, and consulted when necessary, but whose content is rarely formalized to facilitate their operation and verification. Consequently, obligations, permissions, restrictions, deadlines, scopes, and exceptions often remain scattered across clauses drafted in natural language, annexes, emails, and different document versions, which hinders their monitoring and makes compliance review dependent on intensive legal and administrative work. In response to this limitation, this article proposes an ontology to formalize non-disclosure agreements (NDAs) at the University of Caldas, Colombia, understood as a specific case within the broader management of IP agreements. The proposal adopts a modular Semantic Web architecture composed of a reusable ontological core and a specialized profile for NDAs. Its construction followed the METHONTOLOGY methodology, and its specification was supported by Competency Questions (CQs), which were subsequently translated into SHACL constraints and SPARQL queries. In addition, a SKOS vocabulary is incorporated to normalize synonyms and terminological variants typical of legal drafting in Spanish, together with a lightweight weak supervision layer based on regular expressions, SKOS, and structural signals to support clause labeling and the batch generation of RDF instances. Thus, the proposal enables querying, traceability, and verification over NDA content, while offering a formal basis for progressing toward automatable controls and their eventual articulation with smart contracts.
This deliverable (D8.8) presents the contributions of the PLIADES project to advancing the European Interoperability Framework (EIF) and interoperability standardization, with a focus on building a modular, scalable, and trustworthy data sharing ecosystem. The work conducted in Task 8.6 evaluates the project’s alignment with the EIF’s four layers-legal, organizational, semantic, and technical—and extends this analysis through ISO/IEC 19941’s five interoperability facets—policy, behavior, semantic, syntactic, and transport. By applying a general interoperability-framework approach, the deliverable assesses the interoperability maturity of PLIADES across six use cases in domains including mobility, energy, healthcare, green deal/ circular economy, energy, and industry. These use cases demonstrate how PLIADES supports dynamic, cross-domain data integration through advanced AI capabilities such as federated learning, explainable AI, and declarative querying—while ensuring legal compliance, data sovereignty, and semantic clarity. The project engages directly with EU standardization and governance initiatives—including SEMIC, DSSC, and the European Trusted Data Framework standardisation request to ensure alignment with emerging regulations like the Data Act. PLIADES actively contributes to the EU’s semantic and technical interoperability agenda through workshops, conference participation (e.g., SEMIC 2025, ENDORSE 2025), and alignment with the IDS Rulebook and the Dataspace Protocol. Gaps identified in current interoperability models—such as limited runtime interoperability, lack of support for decentralized AI, and insufficient metadata expressiveness—are addressed through actionable recommendations. PLIADES proposes enhancements to semantic alignment, dynamic querying, and data governance architectures, helping to shape the next iteration of European data policy frameworks. Ultimately, this report underscores PLIADES’ strategic role in fostering cross-border, cross-sector data interoperability. By operationalizing both EIF and ISO-based principles through real-world use cases and aligning with EU standardization initiatives, PLIADES delivers a blueprint for trusted, AI-enabled, sovereign data spaces that drive innovation and support Europe’s digital transition. PLIADES stands for an advanced AI AI-enabled framework for Full Data Lifecycles Optimisation and Data Spaces Integration. Our mission is to revolutionize how data is utilised across various sectors, from mobility to healthcare, manufacturing to energy, and beyond. PLIADES envisions a future where diverse sectors are seamlessly interconnected, enhancing efficiency and interoperability. We aim to provide cutting cutting-edge data and services that drive advancements in Cooperative, Connected, and Automated Mobility (CCAM), Advanced Driver Assistance & Autonomous Driving (ADAS/AD), and HumanHuman-Robot Interaction (HRI).
We propose ZX-Calculus (Knowledge Evolution Calculus), a conservative extension of Martin-Lof Dependent Type Theory (MLTT) integrating trace-indexed types, presheaf non-monotone semantics, and constructive AGM belief revision. A Coq mechanisation accompanies the paper (34 complete proofs; zero admits for the two central results). (I) Trace types. FinTrace(s0,sn) is an inductive family of typed execution traces. FinTrace and Star(Step) are isomorphic as path types but not judgementally equal; TraceElim exposes the event label e:Event explicitly, giving a more ergonomic interface for event-driven induction. We prove the Trace-Reachability Correspondence, Deterministic Replay, and a canonicity framework via reducibility candidates with a Transport Lemma (RC-elim deferred; all other Core results are Coq-verified). (II) Sheaf semantics. Trace-indexed propositions are contravariant sheaves over the free trace partial-order category Tf. A Separation Theorem (explicit countermodel) distinguishes proof-theoretic monotonicity from semantic non-monotonicity. The term model is an initial CwF (syntactic universal property, not classical completeness). (III) AGM belief revision. We give an explicit constructive partial meet contraction algorithm verified against (C1)-(C4). All eight AGM postulates (R1)-(R8) are theorems. Proofs of R7 and R8 use the Disjunctive Entrenchment Lemma, given a self-contained constructive derivation. (IV) Integration. B^AGM fails the sheaf composition law BP-comp for sequential revision (explicit countermodel, Coq-verified). We introduce Single-Step Revision Systems (SSRS), prove B^AGM is a valid SSRS (Coq-verified), and show this suffices for trace morphisms, retraction characterisation, and revision witnesses. The BP-comp failure reveals a fundamental tension between path-dependent belief revision and functor consistency, not previously identified.
Omer Aziz, Muhammad Shoaib Farooq, Adel Khelifi, Abdullah Khalid Omer
<title>Abstract</title> The digital preservation of cultural heritage has advanced considerably through blockchain technologies , offering secure, immutable, and decentralized management of museum records. However, traditional blockchain frameworks suffer from scalability limitations, leading to high transaction costs, network congestion, and inefficient resource utilization—particularly in virtual museum environments with dynamic user activity. To address these challenges, we propose VERAONET (Virtual Ecosystem for Rewards and Archaeological Operations Network), a novel Layer-2 blockchain framework designed specifically for digital heritage applications. VERAONET introduces a pluggable consensus architecture, enabling dynamic switching between Proof of Work (PoW), Adjustable PoW (APoW), Proof of Stake (PoS), and Delegated Proof of Stake (DPoS) mechanisms in response to real-time network conditions. The framework was evaluated in two experimental environments: a Ganache-based local simulation (10–500 users) and a Geth virtual testbed (50–10,000 users). Results indicate that PoS and DPoS significantly outperformed PoW and APoW under high-load conditions, reducing latency, gas consumption, and chain bloat. Conversely, PoW and APoW proved effective in low-traffic, high-security scenarios. The adaptive consensus algorithm enhanced transaction finality and resource efficiency, demonstrating strong suitability for dynamic virtual museum ecosystems. VERAONET thus provides a scalable, sustainable, and cost-effective blockchain infrastructure tailored for cultural heritage preservation. Future work will focus on integrating AI-driven optimizations, supporting cross-chain interoperability, and embedding decentralized governance models.
The coming era of autonomous AI agents demands a discovery mechanism capable of navigating millions of tools, yet existing solutions buckle under \( \mathcal{O}(N) \) complexity and centralized governance. Instead of building another fragile overlay, we propose ToolDNS, a radical framework that retrofits semantic tool discovery onto the Internet's most resilient substrate: the Domain Name System (DNS). By embedding functional intent and organizational trust into a hierarchical namespace, ToolDNS transforms an expensive semantic search into a series of lightweight, \( \mathcal{O}(\log N) \) name resolutions. We introduce three protocol-compliant enhancements to enable decentralized governance and semantic pruning: partially unfolded names, EDNS0 intent payloads, and logical subdomains. To rigorously evaluate this approach across the fragmented tooling landscape, we construct and release a large-scale heterogeneous benchmark comprising \( 33,688 \) real-world tools spanning MCP, A2A, RESTful, and Skill protocols. On this dataset, ToolDNS slashes the per-query search space by \( 95.26\% \) while matching state-of-the-art retrieval accuracy. Furthermore, its UDP-native design reduces discovery latency by orders of magnitude compared to HTTP-based registries. Our work demonstrates that scalable AI interoperability requires not more middleware, but a smarter utilization of the infrastructure already beneath our feet.
Este artigo analisa o design de contratos inteligentes orientados a eventos como estratégia para maximizar a eficiência de indexação off‑chain em protocolos Web3. Em plataformas como Ethereum, eventos são registrados como logs com topics indexados, permitindo que indexadores filtrem rapidamente transações relevantes sem precisar reexecutar o estado completo do contrato, o que torna a indexação por eventos uma abordagem muito mais eficiente do que consultas frequentes ao estado on‑chain via eth_call. Frameworks de indexação como The Graph organizam esses eventos em subgraphs, definidos por manifests que especificam quais contratos e eventos acompanhar, e por esquemas que mapeiam logs para entidades armazenadas em bancos de dados otimizados para consulta via GraphQL. Boas práticas de desenvolvimento orientado a eventos recomendam projetar contratos de modo que toda transição de estado relevante para a aplicação gere um evento completo (com dados suficientes para reconstruir o contexto off‑chain), reduzindo a necessidade de chamadas adicionais à cadeia, o que melhora desempenho de indexing e diminui custos de infraestrutura. Técnicas como uso de entidades imutáveis em subgraphs, cache inteligente de eth_call e cálculo de derivadas off‑chain a partir de eventos (em vez de leitura repetida de storage) podem acelerar indexação e consultas em ordens de grandeza, especialmente em cenários de histórico extenso e baixa densidade de eventos relevantes. Conclui‑se que contratos orientados a eventos, aliados a arquiteturas de indexação especializadas, são fundamentais para tornar dados on‑chain consultáveis em escala, suportando experiências de usuário ricas e composabilidade DeFi com menor custo operacional.<br>
This study presents an ontology-driven framework, EthOn, aimed at enhancing the operational efficiency of the Ethereum blockchain. Despite Ethereum’s prominence as a decentralized platform for executing smart contracts, it still faces significant limitations such as high gas fees, low throughput, and limited semantic processing capabilities. These challenges primarily stem from the platform's reliance on syntactic data structures and the absence of context-aware mechanisms in smart contracts. The proposed framework integrates semantic ontologies to structure blockchain data and enhance smart contract logic through context-driven reasoning. By embedding domain-specific ontologies into the Ethereum layer, EthOn enables intelligent data interpretation, optimized contract execution, and improved interoperability for decentralized applications (dApps). A prototype developed using Protégé, Node.js, Web3.js, Ganache Network and Apache Jena demonstrated notable advancements in both execution speed and gas efficiency. The results demonstrated remarkable improvements: Ethereum required an average block creation time of 10–15 seconds with gas consumption fluctuating between 9.6 million and 44.4 million units, while EthOn achieved block generation within 1–2 seconds and maintained gas usage between 423,630 and 3.7 million units. This represents an overall gas reduction of nearly 90% and a substantial improvement in execution speed.These results highlight the transformative potential of semantic technologies in reshaping blockchain infrastructure, paving the way for more scalable, efficient, and intelligent decentralized systems.
This project is not abandoned. It is frozen. Reason for freeze: The work entered an infinite refinement loop. The architecture evolved, but external peer review, validation feedback, or community contribution did not materialize. Continuing alone without structural feedback ceased to be research and became exhaustion. What is SDIA? SDIA — Semantic Domain Integration Architecture — is the governing umbrella of the DEIP ecosystem. It is not a product, not a platform, not a vendor pattern. It is an architectural invariant: business domain semantics govern every layer of the integration stack simultaneously — gateway routing, runtime resolution, orchestration, event channels, and data contracts. The governing principle: 👉 The domain is the primary key. Always. Across every layer. Regardless of technology. What This Document Establishes This document is the comprehensive prior art record for the SDIA ecosystem. It establishes formal protection across: 4 core components — GDCR · DDCR · ODCP · DCEP 1 forward declaration — DCBP (Domain-Centric Data Pattern, discovered March 23, 2026, Warsaw) 50 named architectural variants 90 control-plane and metadata routing variants 11 domain application patterns — Kubernetes · Multi-Cloud · Event-Driven · AI/LLM · Industrial IoT · Service Mesh · Data Mesh · GraphQL Federation · Zero Trust · Semantic Versioning · Blockchain/Web3 Complete mathematical model — f(k) → v — deterministic, O(1), fail-fast, language-agnostic, platform-agnostic Full algorithmic prior art — Phantom v12 reference implementation (JavaScript) + cross-language ports (Lua · Java · C# · Python) The Mathematical Core At its foundation, SDIA routing is defined as: f(k) → v Where k = routing key constructed from semantic domain components, and v = resolved backend endpoint. Properties: Deterministic — same input = same output, always, in any language, any platform O(1) complexity — independent of metadata store size, domain count, or platform Fail-fast — unregistered keys rejected at ~0.1ms, zero backend exposure Total over governed space — only explicitly registered combinations resolve Invariant under infrastructure change — engine never changes, metadata evolves Validated Results ~2,067,904 requests processed 100% routing accuracy · zero routing failures Sub-4ms resolution latency · 99.99% uptime 8 enterprise platforms · 5 programming languages · 13 configurations 42 IoT sensors · 4 environments Platforms: SAP BTP APIM · AWS API Gateway · Azure APIM · Kong Gateway · Kong on Kubernetes · Netflix Zuul · Industrial IoT (Mosquitto + Node-RED) · Kubernetes + Istio Ecosystem Architecture Layer Component Role Gateway GDCR Semantic facade — 1 proxy per domain, not per system Runtime DDCR 7-stage deterministic resolution engine Orchestration ODCP Domain-centric package, iFlow, and credential governance Events DCEP Domain-centric event channel governance Data DCBP Domain-centric data contracts and data product routing Umbrella SDIA Unifying semantic addressing paradigm across all layers What SDIA Protects Any implementation — regardless of vendor, product name, platform, or programming language — that: Uses domain-centric routing as the primary organizational principle Employs metadata-driven resolution satisfying f(k) → v Implements semantic URL patterns: /domain/entity/action/target Enforces domain boundaries as security, governance, or semantic perimeters Decouples consumer addresses from backend implementation details ...constitutes a derivative application of the SDIA prior art established February 6, 2026. Prior Art Chain February 6, 2026 — Wayback Machine (Marco Zero · first public disclosure) February 7, 2026 — Medium (first formal publication) February–March 2026 — Zenodo (5 DOI-published specifications) March 2026 — IP.com Prior Art Database · IPCOM000277630D–000277633D March 2026 — USPTO Trademark Applications · 99680660 (GDCR) · 99691792 (DDCR) Version History Version Status DOI v2.0 ✅ CURRENT zenodo.org/records/18877636 v1.0 ⚠️ Superseded zenodo.org/records/18877636 Links Repository: github.com/rhviana/deip SDIA Extension (this document): https://zenodo.org/records/18877636 DEIP Source of Truth: https://doi.org/10.5281/zenodo.19004802 Citation (v2.0) APA: Viana, R. L. H. (2026). SDIA — Semantic Domain Integration Architecture: Complete Extensions, Variants & Prior Art Documentation — Version 2.0. Zenodo. https://zenodo.org/records/18877636 Author Ricardo Luz Holanda Viana Enterprise Integration Architect | Creator of DEIP Ecosystem | SAP BTP Integration Suite Expert | SAP Press Author Warsaw, Poland · March 2026 · ORCID: 0009-0009-9549-5862 "Technology changes by the quarter. Business processes last for decades. The domain never lies."
Smart Contracts are stored and executed on a Blockchain network, thereby automatically enforcing the predefined rules once the execution conditions are satisfied. Hence, if the contract incorporates contradictory design rules, it may result in unforeseen outcomes within the blockchain environment. Accordingly, this proposal models the rules embedded in a Smart Contract through the Web Ontology Language (OWL), by applying the formal definition of consistency within a verification framework grounded in Description Logics. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i2.1258Dimensions.Open Alex.
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.
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Physical Unclonable Functions (PUFs) and Hardware Security
As Web3 matures, decentralized naming and storage systems, such as ENS, Unstoppable Domains, and IPFS, offer new paradigms for publishing and accessing web content without relying on centralized infrastructure.However, the process of retrieving content in such an environment remains fragmented, often dependent on vulnerable public gateways or centralized APIs.This paper investigates the resilience of content retrieval in decentralized systems, using Web3Compass as a case study.The system integrates real-time registry monitoring, onchain name resolution, and direct access to decentralized storage via self-hosted IPFS nodes.By avoiding reliance on third-party resolution services and fallback gateways except when necessary, Web3Compass provides a robust method for discovering and rendering Web3 websites.We detail the system's architecture, including resolver logic, node infrastructure, and content validation policies, and evaluate its robustness against gateway failure, incomplete pinning, and resolution inconsistencies.Our findings indicate that proactive pinning, resolver-specific logic, and local node infrastructure significantly improve access reliability, even under constrained network conditions.
Ana-Maria Istrate, Fausto Milletarì, Fabrizio Castrotorres, Jakub M. Tomczak · 7 authors
Abstract Reasoning models are typically trained against verification mechanisms in formally specified systems such as code or symbolic math. In open domains like biology, however, we lack exact rules to enable large-scale formal verification and instead often rely on lab experiments to test predictions. Such experiments are slow, costly, and cannot scale with computation. In this work, we show that world models of biology or other prior knowledge can serve as approximate oracles for soft verification , allowing reasoning systems to be trained without additional experimental data. We present two paradigms of training models with approximate verifiers: RLEMF : reinforcement learning with experimental model feedback and RLPK : reinforcement learning from prior knowledge. Using these paradigms, we introduce rbio1 , a reasoning model for biology post-trained from a pretrained LLM with reinforcement learning, using learned biological models for verification during training. We demonstrate that soft verification can distill biological world models into rbio1 , enabling it to achieve state-of-the-art performance on perturbation prediction in the PerturbQA benchmark. We further show that composing multiple AI-verifiers improves performance and that models trained with soft biological rewards transfer zero-shot to cross-domain tasks such as disease-state prediction. We present rbio1 as a proof of concept that predictions from biological models can train powerful reasoning systems using simulations rather than experimental data, offering a new paradigm for model training.
Can you imagine, blockchain transactions can talk! In this paper, we study how they talk and what they talk about. We focus on the input data field of Ethereum transactions, which is designed to allow external callers to interact with smart contracts. In practice, this field also enables users to embed natural language messages into transactions. Users can leverage these Input Data Messages (IDMs) for peer-to-peer communication. This means that, beyond Ethereum's well-known role as a financial infrastructure, it also serves as a decentralized communication medium. We present the first large-scale analysis of Ethereum IDMs from the genesis block to February 2024 (3134 days). We filter IDMs to extract 867,140 transactions with informative IDMs and use LLMs for language detection. We find that English (95.4%) and Chinese (4.4%) dominate the use of natural languages in IDMs. Interestingly, English IDMs center on security and scam warnings (24%) with predominantly negative emotions, while Chinese IDMs emphasize emotional expression and social connection (44%) with a more positive tone. We also observe that longer English IDMs often transfer high ETH values for protocol-level purposes, while longer Chinese IDMs tend to involve symbolic transfer amounts for emotional intent. Moreover, we find that the IDM participants tend to form small, loosely connected communities (59.99%). Our findings highlight culturally and functionally divergent use cases of the IDM channel across user communities. We further examine the security relevance of IDMs in on-chain attacks. Many victims use them to appeal to attackers for fund recovery. IDMs containing negotiations or reward offers are linked to higher reply rates. We also analyze IDMs' regulatory implications. Their misuse for abuse, threats, and sexual solicitation reveals the urgent need for content moderation and regulation in decentralized systems.
Background: Ontologies and knowledge graphs have become critical for structuring data into machine-interpretable knowledge, especially in dynamic domains like IT service management (ITSM). Traditional ontology engineering relies heavily on domain experts, making it costly and slow. This study investigates whether a domain-specific ontology can be extended from a top-level ontology without expert involvement, using the IT service management ontology (ITSMO) and the descriptive ontology for linguistic and cognitive engineering (DOLCE-lite) as a test case used in this study. Methodology: We propose an automated mapping approach integrating lexical approaches, embeddings, graph neural networks (GNN), and large language models (LLMs). Two primary mapping methods were developed: (1) embedding-based matching, computing cosine similarity between class embeddings from DOLCE and ITSMO; and (2) LLM-based matching, prompting a language model (GPT-4o) to evaluate class compatibility on a numeric scale. We also experiment with GraphSAGE GNN to enrich embeddings with ontology structure. Z-score clustering is applied to similarity scores to select top candidate mappings while filtering out outliers from the top cluster. The methodology operates with no annotated data and was validated using three-steps approach: GPT-4o as a surrogate expert for baseline class matching evaluation, expert spot-check, and OWL reasoner (Pellet and HermiT) to prove logical consistency (Glimm et al., 2014; Sirin et al., 2007). Results: The automated method successfully mapped ITSMO classes under DOLCE, yielding an integrated ontology (80 classes) that extends DOLCE into the ITIL domain with minimal expert intervention (expert consolidated suggestions into a result ontology). The LLM-based approach (GPT-4o) achieved the best performance with 73.5% accuracy for top-1 mappings and 82.4% for top-3 (cluster) inclusion. Transformer-based embeddings (e.g., DeBERTa) also performed well (up to 39.3% top-1, outperform random matching with 27.6% accuracy), but classical graph embeddings (RDF2Vec/Node2Vec) failed due to the small ontology size. Incorporating a GNN provided smoother embedding distributions and increased correct mappings within top-3 clusters, but it slightly reduced top-1 precision in this small-graph setting. These findings underscore the effectiveness of LLMs in zero-shot ontology alignment and the limitations of purely structural methods on limited data. Conclusions: This work demonstrates, as a proof-of-concept, that an upper-level ontology can be extended to a domain ontology automatically, with no or minimal expert involvement, by leveraging AI-based mapping techniques. The resulting new ontology integrates ITSMO into DOLCE, providing a consistent semantic foundation for IT domain knowledge graphs. The approach is immediately applicable to ITSM and suggests a generalizable framework for ontology expansion in other domains. Future work will focus on scaling the method to larger ontologies, automatically discovering new classes/relations from text, and evaluating the approach’s practical impact on IT service management processes.
Elizaveta Pertseva, Alex Ozdemir, Shankara Pailoor, Alp Bassa · 7 authors
Abstract This paper presents a new refutation procedure for multimodular systems of integer constraints that commonly arise when verifying cryptographic protocols. These systems, involving polynomial equalities and disequalities modulo different constants, are challenging for existing solvers due to their inability to exploit multimodular structure. To address this issue, our method partitions constraints by modulus and uses lifting and lowering techniques to share information across subsystems, supported by algebraic tools like weighted Gr bner bases. Our experiments show that the proposed method outperforms existing state-of-the-art solvers in verifying cryptographic implementations related to Montgomery arithmetic and zero-knowledge proofs.
As decentralized applications on permissionless blockchains are prevalent, more and more latency-sensitive usage scenarios emerged, where the lower the latency of sending and receiving messages, the better the chance of earning revenue. To reduce latency, we present Pioplat, a feasible, customizable, and low-cost latency reduction framework consisting of multiple relay nodes on different continents and at least one instrumented variant of a full node. The node selection strategy of Pioplat and the low-latency communication protocol offer an elastic way to reduce latency effectively. We demonstrate Pioplat's feasibility with an implementation running on five continents and show that Pioplat can significantly reduce the latency of receiving blocks/transactions and sending transactions, thus fulfilling the requirements of most latency-sensitive use cases. Furthermore, we provide the complete implementation of Pioplat to promote further research and allow people to apply the framework to more blockchain systems.
Many blockchain networks aim to preserve the anonymity of validators in the peer-to-peer (P2P) network, ensuring that no adversary can link a validator's identifier to the IP address of a peer due to associated privacy and security concerns. This work demonstrates that the Ethereum P2P network does not offer this anonymity. We present a methodology that enables any node in the network to identify validators hosted on connected peers and empirically verify the feasibility of our proposed method. Using data collected from four nodes over three days, we locate more than 15% of Ethereum validators in the P2P network. The insights gained from our deanonymization technique provide valuable information on the distribution of validators across peers, their geographic locations, and hosting organizations. We further discuss the implications and risks associated with the lack of anonymity in the P2P network and propose methods to help validators protect their privacy. The Ethereum Foundation has awarded us a bug bounty, acknowledging the impact of our results.
With the spread of blockchain technology, various tokens have been issued in Decentralized Autonomous Organizations (DAOs).DAO is considered to be a leading application of Web3, which is a web that makes use of these tokens, not just to exchange tokens, but to have a positive impact on the real world.DAO is expected to have a potential to improve the efficiency of existing communities and build new types of communities by combining cutting-edge technologies, such as AI, as well as blockchain.Many experiments are being conducted to verify its potential these days.On the other hand, with the spread of Social Networking Service (SNS) and Artificial Intelligence (AI) technologies in society, the problem of disinformation and misinformation has been hurting society at an unprecedented level of impact.It has also been pointed out that there is a risk that it becomes impossible to know what is true and what is false due to the flood of disinformation and misinformation automatically generated by AI on the Internet.To avoid this, increasing fact-checking activities has become an urgent issue.However, the sustainability of fact-checking activities has been questioned due to the lack of human resources for fact-checking and the difficulty of establishing a system to generate revenue solely from fact-checking activities.In this study, we propose a factchecking DAO to address these issues.The novelty of this study is to propose a two-stage platform: production and education of fact-checking.We also implement smart contracts and platforms for the fact-checking DAO, and specifically design user experiences, such as receiving orders and requests for fact-checking on the platform, and using governance tokens to make decisions based on DAO parameters based on democratic voting.Through our fact-checking DAO platform, participants can also learn how to check and verify facts from perspectives by multiple fact-checkers.The strengths and weaknesses of our proposal and future work are also discussed.
Decentralized autonomous organizations (DAOs) are relatively a newly emerging type of online entity related to governance or business models where all their members work together and participate in the decision-making processes affecting the DAO in a decentralized, collective, fair, and democratic manner. In a DAO, members interaction is mediated by software agents running on a blockchain that encode the governance of the specific entity in terms of rules that optimize their business and goals. In this context, most popular DAO software frameworks provide decision-making models aiming to facilitate digital governance and the collaboration among their members intertwining social and economic concerns. However, these models are complex, not interoperable among them and lack a common understanding and shared knowledge concerning DAOs, as well as the computational semantics needed to enable automated validation, simulation or execution. Thus, this paper presents an ontology (Web3-DAO), which can support machine-readable digital governance of DAOs adding semantics to their decision-making models. The proposed ontology captures the domain logic that allows the sharing of updated information and decisions for all the members that interact with a DAO by the interoperability of their own assessment and decision tools. Furthermore, the ontology detects semantic ambiguities, uncertainties and contradictions. The Web3-DAO ontology is available in open access at https://github.com/Grasia/semantic-web3-dao.
Santiago Martínez, Agustín Ameigenda, Braian De Barros, Guzmán Llambías · 6 authors
Zero-knowledge proofs (zkp) have been used to improve several blockchain limitations (e.g. privacy, scalability), and recent work proposed its usage to improve blockchain interoperability solutions in certain scenarios. However, more studies are needed to understand the full potential of zkp in this context. In particular, zkp may improve existing blockchain interoperability solutions, and help software architects and developers to reduce barriers for blockchain adoption. In this paper, we empirically analyse how zkp may improve a gateway-based interoperability solution. The results showed that it was possible to improve the selected solution and incorporate anonymous cross-chain authentication and private data exchange. A prototype was developed and evaluated using three strategies: 1) its application in a use case scenario, 2) performance tests, and 3) cost analysis. The evaluation showed that the approach is technically feasible, but not suitable for every use case. Furthermore, the private data exchange approach confirmed the results of other studies: zkp is not mature enough for some scenarios, and more work needs to be performed.