This paper repositions the polymath as a central figure within the networked and decentralized landscape of contemporary knowledge production and distribution, reflecting on the changing states of remix culture with emergent technologies like Web3. The polymath is reconceptualized as a “DJ of Thought,” engaging in transdisciplinary remix practices that challenge conventional notions of authorship and intellectual ownership. Drawing on Michel de Certeau’s concept of everyday tactics and strategies of subversion and appropriation, the chapter examines how the polymath navigates and disrupts dominant knowledge systems through remix acts. The polymath is portrayed as a creative agent, materially manifesting knowledge through transdisciplinary remix techniques. This approach highlights the tension between the polymath’s agency in remix culture and the influence of “more-than-human” entities, such as technological infrastructures and generative models, on knowledge creation. The chapter challenges traditional knowledge hierarchies and fosters an understanding of authorial agency in the digital age, emphasizing multi-authored knowledge artifacts. It contributes to discussions on the political dimensions of remix culture and the evolving role of distributed authorship in shaping knowledge, underscoring the polymath’s capacity for creative resistance and intellectual engagement.
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 blockchain and distributed ledger technologies continue to evolve, the management of digital identity ownership and its security have increasingly come under scrutiny. The advent of decentralized identity (DID) technologies aims to return control of identity to users. However, existing DID resolution schemes often rely on centralized management, which can lead to single points of failure, security vulnerabilities, insufficient scalability, and privacy concerns. To address these challenges, this paper introduces a novel solution named CMS. CMS leverages blockchain smart contracts and InterPlanetary File System (IPFS) decentralized storage to implement a consortium management approach. It drives the management of a universal resolver through a voting mechanism of smart contracts and utilizes IPFS for distributed storage, thereby enhancing system transparency, stability, and the persistent security of data. Although this approach increases the technical complexity of the system and may impact performance, it significantly enhances management transparency and data security.
Due to security risks such as data theft, data tampering, and replay attacks during data sharing, data owners need to establish a trust relationship before sharing their data. To reduce the burdens of data retrieval, how to generate an efficient and secure index has become a challenge. Crypto-based solutions currently only encrypt the data to ensure confidentiality, which ignore the integrity and correctness of the sharing data. An hash-based authentication structures called Merkle Tree is an effective tool for data integrity verification. However, it incurs high maintenance costs when dealing with dynamically changing datasets and is limited by data modalities. In this paper, we propose a trustworthy index for multimodal data sharing (MT-Index). Specifically, we propose a Merkle tree based on the Semantic Web, replacing traditional data labels with semantic graphs to represent the content of data blocks. We utilize timestamp to mark the update operations and store them in the leaf nodes of the tree, so as to effectively handle multimodal data and dynamic dataset changes. Additionally, we design a trust network based on zero-knowledge proofs, utilizing ZK-STARKs to ensure the credibility of one-to-one interactions, and implement a two-round protocol to verify the trust mechanism among multiple parties. Through formal analysis, we demonstrate that MT-Index achieves the desired security objectives with minimal storage and generation overhead.
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.
The group signature with designated traceability (GSdT) is a kind of group signatures (GS) which aim to restrict the opening authority of the group manager; by setting an access structure over openers’ attributes at the signing, a signer is able to control openers who can open the signature. A generic construction of GSdT was given when the notion was introduced, then a pairing-based construction and a symmetric-key-based one were presented. Nonetheless, it remains open whether or not a post-quantum GSdT that has full anonymity can be really constructed.In this paper, we give a lattice-based GSdT scheme that has full anonymity for the first time. In our construction, the lattice-based ciphertext-policy attribute-based encryption (CP-ABE) by Tsabary and the lattice-based group signatures (GS) by Libert et al. are employed. The CP-ABE is based on the Regev public-key encryption, while the GS uses a non-interactive zero-knowledge proof to prove the correctness of the encryption in the signing process. Based on the compatibility, we combine and modify them to build up a GSdT scheme.
Junyi Zhong, Thiago Abreu, Sami Souihi, Françoise S. Lucas
This paper introduces the G-TOK framework, which utilizes advanced zero-knowledge proofs (ZKPs) and dynamic verifiable credentials (VCs) to preserve data privacy in sensor data sharing on blockchain networks. As industries increasingly depend on accurate and confidential sensor data from IoT applications, maintaining privacy and data integrity becomes a significant challenge. Our framework specifically addresses this issue in the context of smart environment sensor networks. Typically, data access control in such networks is either fully permissioned or overly restrictive, lacking mechanisms for selective disclosure access control. Our approach aims to enhance encrypted decentralized data storage and improve data interoperability. It includes dynamic VCs, authenticated privacy-preserving tokenization of geolocation data, and a decentralized real-time location verification scheme. Additionally, we propose a proof-of-footprint (PoF) schema, showcasing the integration and practicality of cutting-edge technologies such as ZKPs, VCs, and self-sovereign identities. This schema aligns with international standards, including the Verifiable Credentials Data Model v2.01and selective disclosure of JSON Web Token (JWT) claims2.
In today’s digital age, the verification of documents is a critical aspect of numerous transactions and processes across various industries. However, traditional methods of document verification are often susceptible to fraud, tampering, and inefficiencies. In response to these challenges, this project proposes a novel solution leveraging blockchain technology to enhance the security and integrity of document verification processes. The objective of this project is to develop a decentralized system for document verification using blockchain, aiming to provide a secure, transparent, and tamper-proof platform for verifying the authenticity of digital documents. By harnessing the immutable and transparent nature of blockchain, the proposed system seeks to address the shortcomings of traditional verification methods and establish a trusted environment for document verification. Key features of the proposed system include the use of cryptographic hashing techniques to create unique digital fingerprints for each document, which are then stored on a blockchain network. Smart contracts are utilized to automate the verification process, enabling seamless and transparent verification without the need for intermediaries.The methodology involves the design and implementation of the blockchain-based document verification platform, incorporating essential components such as user authentication, document uploading, verification, and retrieval functionalities. The system is developed using Ethereum, a popular blockchain platform, and is deployed on a test network for evaluation and testing. Results from experimental testing demonstrate the effectiveness and reliability of the proposed system in providing tamper-proof document verification services. Furthermore, comparative analysis with existing centralized solutions highlights the advantages of blockchain-based verification in terms of security, transparency, and efficiency.
2 source records
Web Data Mining and Analysis
Semantic Web and Ontologies
Mathematics, Computing, and Information Processing
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.
A group signature scheme in which signers are able to designate openers by specifying access structures over openers' attributes was introduced at CANDAR 2021, which is called GSdT. In this paper, we present a construction of GSdT from only symmetric-key primitives; pseudorandom functions, hash functions and commitments. Due to the features, our GSdT is expected to be secure against computational power of quantum computers. We first introduce syntax and security definitions in the static group model. Then, in our construction, the key ingredient is a non-interactive zero-knowledge proof of knowledge system that is constructed from the primitives in the “MPC-in-the-head” paradigm, owing the technique that was developed by Katz, Kolesnikov and Wang (ACM-CCS 2018). Our approach starts with their group signature scheme, but non-trivially extends the Merkle tree so that signers can treat (all-AND) boolean formulas as the access structures. According to our estimation, the signing time is less than 3.0 sec and the signature size is less than 0.5 MB in a scenario that the numbers of group members and attributes are 27and 23, respectively, and security to be attained is 128 bit quantum security.
Managing accounts in a multi-chain environment is complex, with both challenges and opportunities. This paper introduces a novel multi-chain account management system designed to navigate these complexities, enabling informed decisions and active engagement with diverse communities and projects. The system bridges account data and community information across chains, promoting seamless participation and fostering engagement, regardless of the underlying blockchain. This enhanced interoperability expands access to different chains, unlocking their unique strengths. While offering substantial benefits, the system's evolution is ongoing. Future areas include scalability, interoperability standards, privacy solutions, and user experience improvements. The system simplifies decision-making and engagement across communities. As the blockchain ecosystem evolves, it lays the groundwork for effective multi-chain account management, particularly for DAOs. Facilitating user adoption and engagement requires informative resources to harness each blockchain's unique attributes. In summary, effective management of cross-chain communities between Ethereum and compatible blockchains necessitates a holistic approach combining technical infrastructure, transparent communication, and robust governance.
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.
The global transition towards Web3 is giving rise to many blockchain networks, each with its native cryptocurrency. Ethereum is used for decentralized applications, Bitcoin is used for investment, and Polygon is used for scalability solutions. Furthermore, a few well-known blockchain platforms have implemented interoperability features, meaning users can now send wrapped tokens around different blockchains. User assets are then distributed across multiple blockchain networks and wallets. This means user assets are already distributed across multiple tokens on different blockchain networks. This work presents a web application that allows you to visualize your assets distributed across different blockchain networks and wallets. Notably, this work supports the straightforward integration of secondary wallets with user accounts. In addition, this work supports tracking the historical user asset transfer requests, including incoming and outgoing ones, and storing the metadata associated with each asset transfer, including its corresponding proof’s Content Identifier (CID) after zkSNARKs proof generation by hosting it on the InterPlanetary File System (IPFS).
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.
Decentralised ledgers are gaining momentum following the interest of industries and people in smart contracts. Major attention is paid to blockchain applications intended for trading assets that exploit digital cryptographic certificates called tokens. Particularly relevant tokens are the non-fungible tokens (NFTs), namely, unique and non-replicable tokens used to represent the cryptographic counterpart of assets ranging from pieces of art through to licenses and certifications. A relevant consequence of the hard-coded nature of blockchains is the hardness of probing, in particular when advanced searchers involving the capabilities of the smart contracts or the assets digitised by NFTs are required. For this purpose, a formal representation for the operational semantics of smart contracts and of tokens has become particularly urgent, especially in economy and finance, where blockchains become increasingly relevant. Hence, we feel the need to tailor Semantic Web technologies to achieve that semantic representation at least for NFTS. This article reports on an ontology that leverages the Ontology for Agents, Systems, and Integration of Services (“OASIS”) towards the semantic representation of smart contracts responsible for managing ERC721-compliant NFTs and running on the Ethereum blockchain. Called Ether-OASIS, the proposed ontology adopts OASIS and tailors its behaviouristic approach to the Ethereum blockchain by conceiving smart contracts as agents running on the blockchain and, consequently, smart contract interactions as agent commitments. Smart contracts are represented in terms of their actions, purposes and tokens that they manage, thus realising a blockchain that is more usable both by users and automated applications. The ontology is evaluated using standard ontological metrics and applied on a case study concerning the minting and transferring of NFTs that digitise batches of wheat.
Web3 needs complex semantic frameworks to update, validate, and regulate data across decentralized networks as it grows. The whole semantic system of this study includes SV, SC, DOC, ISV, and SG. The Semantic Validation technique performs parametric validation, scoring, and threshold comparison to safeguard data integrity, whereas the Semantic Agreement algorithm combines meanings by adding agreement values. Decentralized ontologies are improved using Distributed Ontology Construction to accommodate new meaning linkages. connected Semantic Verification detects semantic meaning compatibility across linked networks. Lastly, meaning Governance enables individuals to decide on recommended meaning modifications without centralization. Comparative analysis examines the framework. Tables and illustrations indicate its dominance over key aspects. The recommended strategy generally outperforms Web3 evolution methods in security, scale, interoperability, user privacy, and government effectiveness. Visualizing the process with pie charts, layered analysis, and temporal trends shows its efficacy. This semantic framework's consistency, correctness, and flexibility are key responses to Web3's changes. The framework's continual refinement methods can shape Web3 Internet semantics as open networks change. This semantic framework helps establish a decentralized and connected Internet as bitcoin and Web3 technologies progress. It also allows Web3-aligned semantic development.
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.
Abstract: In the era of digital innovation, Artificial Intelligence (AI) has emerged as a pivotal catalyst, unlocking new avenues for the evolution of Web 3.0. Web 3.0 signifies the next phase of the internet, characterized by decentralized structures, peer-topeer networks, and cutting-edge technologies like blockchain and smart contracts. This research provides an in-depth exploration of the role played by AI in shaping Web 3.0, delving into both its opportunities and challenges. AI proves instrumental in processing and analysing vast datasets with increased efficiency, fostering intelligent decision-making and insightful outcomes. The paper extensively covers essential Web 3.0 concepts and technologies, encompassing the Semantic Web and ontologies, and underscores AI's transformative potential across diverse industries such as healthcare, finance, and education. An analysis of the challenges posed by AI in the Web 3.0 landscape, including issues of data privacy, bias, trust, and ethics, is presented. Furthermore, the research examines the broader societal implications of AI in Web 3.0. Conclusively, the paper outlines future directions and implications of AI within the Web 3.0 framework, proposing potential areas for subsequent research. By contributing to a comprehensive understanding of AI's impact on web development and its broader societal implications, this research aims to guide future endeavours in this dynamic field.
Open access
Blockchain Technology Applications and Security
Artificial Intelligence in Healthcare and Education
Electronic commerce and finance are progressively supporting and including decentralized, shared and public ledgers such as the blockchain. This is reshaping traditional commercial activities by advancing them towards Decentralized Finance (DeFi) and Commerce 3.0, thereby supporting the latter’s potential to outpace the hurdles of central authority controllers and lawgivers. The quantity and entropy of the information that must be sought and managed to become active participants in such a relentlessly evolving scenario are increasing at a steady pace. For example, that information comprises asset or service description, general rules of the game, and specific technologies involved for decentralization. Moreover, the relevant information ought to be shared among innumerable and heterogeneous stakeholders, such as producers, buyers, digital identity providers, valuation services, and shipment services, to just name a few. A clear semantic representation of such a complex and multifaceted blockchain-based e-Commerce ecosystem would contribute dramatically to make it more usable, namely more automatically accessible to virtually anyone wanting to play the role of a stakeholder, thereby reducing programmers’ effort. However, we feel that reaching that goal still requires substantial effort in the tailoring of Semantic Web technologies, hence this article sets out on such a route and advances a stack of OWL 2 ontologies for the semantic description of decentralized e-commerce. The stack includes a number of relevant features, ranging from the applicable stakeholders through the supply chain of the offerings for an asset, up to the Ethereum blockchain, its tokens and smart contracts. Ontologies are defined by taking a behaviouristic approach to represent the various participants as agents in terms of their actions, inspired by the Theory of Agents and the related mentalistic notions. The stack is validated through appropriate metrics and SPARQL queries implementing suitable competency questions, then demonstrated through the representation of a real world use case, namely, the iExec marketplace.