Cynthia Jayapal, Arunmadhavan Evr, G. S. Ajay Adithya, R Raajakishore · 5 authors
Digitization has been an important driver of change and has influenced the mode of operation of universities. However, the certificates of graduates are still paper-based and do not fit into the employer’s digitized recruitment process. The digitization of certificates has long been postponed and has not adopted to the digitized process of employers and universities. Further research on this topic shows that multiple industries will benefit from a digitized process that prevents forged certificates from degrading the value of legitimate recipients and issuing institutions. This paper aims to present a systematic literature review of current distributed ledger technology-based solutions and propose a new type of digital certificate that is hashgraph based to prevent fraud and counterfeiting.
Individuals and organizations are using databases to store personal information at an unprecedented rate. This creates a quandary for data providers. They are responsible for protecting the privacy of individuals described in their database. On the other hand, data providers are sometimes required to provide statistics about their data instead of sharing it wholesale with strong assurances that these answers are correct and complete such as in regulatory filings for the US SEC and other goverment organizations. We introduce a system, ZKSQL , that provides authenticated answers to ad-hoc SQL queries with zero-knowledge proofs. Its proofs show that the answers are correct and sound with respect to the database's contents and they do not divulge any information about its input records. This system constructs proofs over the steps in a query's evaluation and it accelerates this process with authenticated set operations. We validate the efficiency of this approach over a suite of TPC-H queries and our results show that ZKSQL achieves two orders of magnitude speedup over the baseline.
The problem of distributed consensus has played a major role in the development of distributed data management systems. This includes the development of distributed atomic commit and replication protocols. In this monograph, we present foundations of consensus protocols and the ways they were utilized to solve distributed data management problems. Also, we discuss how distributed consensus contributes to the development of emerging blockchain systems. This includes an exploration of consensus protocols and their use in systems with malicious actors and arbitrary faults. Our approach is to start with the basics of representative consensus protocols where we start from classic consensus protocols and show how they can be extended to support better performance, extended features, and/or adapt to different system models. Then, we show how consensus can be utilized as a tool in the development of distributed data management. For each data management problem, we start by showing a basic solution to the problem and highlighting its shortcomings that invites the utilization of consensus. Then, we demonstrate the integration of consensus to overcome these shortcomings and provide desired design features. We provide examples of each type of integration of consensus in distributed data management as well as an analysis of the integration and its implications.
Millions of individuals today utilize cryptocurrencies, which have a strong open-source community and payment network. The first study to predict cryptocurrency prices using news and social media emotion was published in In this paper, we apply sentiment analysis and machine learning principles to find the correlation between "public sentiment" and "market sentiment". We use twitter data to predict public mood and use the predicted mood and cryptocurrency financial news to predict the market movements.
In the development of large-scale, integrated systems, the consistent clarity and distribution of knowledge and relevant status is crucial to success. There are many existing methods and commercial tools for providing context and traceability from requirements and specifications to a system's artifacts, but these tools are often vendor-locked and require access to cloud-based services and necessitate high licensing costs. Further, modern large-scale systems development involves multiple business partners, each of which needs to ensure their teams have granular, role-based access to all relevant information without impediment; centralized warehousing and gatekeeping should not be handled by a single entity if the information is to remain readily accessible. Instead, a permissioned, distributed knowledgebase that avoids vendor lock-in enables a consistent, real-time view of information that provides equivalent context for developers and other stakeholders. ChaordicLedger, a free and open source (FOSS) project joins the transparency and smart contract aspects of Distributed Ledger Technology with the storage capabilities of a Distributed File System to fulfill this industrial application while allowing for industry-specific customizations.
Priyanka Pandit, Daniel Nevius, Vibhav Srivaths, Mihai Diaconeasa
Abstract The Nuclear Power Plant (NPP) project lifecycle consists of multiple organizations, private and public, that work together to carry out the licensing and regulation, commissioning, construction, supply chain management, decommissioning, and non-proliferation of nuclear power plants. Each stage of the lifecycle generates a considerable amount of documentation that needs to be archived and made available on request. In this paper, we examined the current frameworks employed by the stakeholders of nuclear power plant lifecycles for data generation, classification, archival, and exchange and we evaluated the use of distributed ledger technology for data management. We further demonstrated the implementation of distributed ledger technology to capturing and immutable recording nuclear supply chain structure, production, and failure data. Distributed Ledger Technology (DLT) promises to address the current bottlenecks in the lifecycle management of nuclear power plants with faster data exchange times, lower processing cost of documents, bridging the gap between perceived and actual risk, faster decisions, customizable transparency in job tasks being executed, improved cash flow, instant validation of job completion, reduction in logistical friction, and sped up supply chain decisions for clients. We gave a comprehensive review of distributed ledger technology, its properties and an open-source permissioned distributed ledger system called Hyperledger Fabric. Each sector of the nuclear power plant lifecycle was analyzed for data management bottlenecks and building on our discussion of employing distributed ledger technology we discussed the pathway in which Hyperledger Fabric can be employed to address the data management bottlenecks in each stage of the lifecycle including, licensing and regulation, commissioning, construction, supply chain management, decommissioning, and non-proliferation.
AI requires heavy amounts of storage and compute. As a result, AI developers are regular users of centralised cloud services such as AWS, GCP and Azure, compute environments such as Jupyter and Colab notebooks, and AI Hubs such as HuggingFace and ActiveLoop. There services are associated with certain benefits and limitations that stem from the underlying infrastructure and governance systems with which they are built. These limitations include high costs, lack of monetization and reward, lack of control and difficulty of reproducibility. At the same time, there are few libraries that allow data scientists to interact with decentralised storage in the language that data scientists are used to, and few hubs where they can discover and interact with AI assets. In this report, we explore the potential of decentralized technologies - such as Web3 wallets, peer-to-peer marketplaces, decentralized storage (IPFS and Filecoin) and compute, and DAOs - to address some of the above limitations. We showcase some of the libraries and integrations that we have built to tackle these issues, as well as a proof of concept of a decentralized AI Hub app, that all use IPFS as a core infrastructural component.
Daniël Reijsbergen, Aung Htein Maw, Zheng Yang, Tien Tuan Anh Dinh · 5 authors
Users today expect more security from services that handle their data. In addition to traditional data privacy and integrity requirements, they expect transparency, i.e., that the service's processing of the data is verifiable by users and trusted auditors. Our goal is to build a multi-user system that provides data privacy, integrity, and transparency for a large number of operations, while achieving practical performance. To this end, we first identify the limitations of existing approaches that use authenticated data structures. We find that they fall into two categories: 1) those that hide each user's data from other users, but have a limited range of verifiable operations (e.g., CONIKS, Merkle2, and Proofs of Liabilities), and 2) those that support a wide range of verifiable operations, but make all data publicly visible (e.g., IntegriDB and FalconDB). We then present TAP to address the above limitations. The key component of TAP is a novel tree data structure that supports efficient result verification, and relies on independent audits that use zero-knowledge range proofs to show that the tree is constructed correctly without revealing user data. TAP supports a broad range of verifiable operations, including quantiles and sample standard deviations. We conduct a comprehensive evaluation of TAP, and compare it against two state-of-the-art baselines, namely IntegriDB and Merkle2, showing that the system is practical at scale.
Ulysse Pavloff, Yackolley Amoussou-Guenou, Sara Tucci-Piergiovanni
Ethereum has undergone a recent change called \textit{the Merge}, which made Ethereum a Proof-of-Stake blockchain, shifting closer to BFT consensus. Ethereum, which wished to keep the best of the two protocol designs (BFT and Nakomoto-style), now has a convoluted consensus protocol as its core. The result is a blockchain being possibly produced in a tree-like form while participants try to finalize blocks. We categorize different attacks jeopardizing the liveness of the protocol. The Ethereum community has responded by creating patches against some of them. We discovered a new attack on the patched protocol. To support our analysis, we propose a new high-level formalization of the properties of liveness and availability of the Ethereum blockchain, and we provide a pseudo-code. We believe this formalization to be helpful for other analyses as well. Our results yield that the Ethereum Proof-of-Stake has safety but only probabilistic liveness. The probability of the liveness is influenced by the parameter describing the time frame allowed for validators to change their mind about the current main chain.
In the past few years, the main research efforts regarding General Data Protection Regulation (GDPR)-compliant data sharing have been focused primarily on informed consent (one of the six GDPR lawful bases for data processing). In cases such as Business-to-Business (B2B) and Business-to-Consumer (B2C) data sharing, when consent might not be enough, many small and medium enterprises (SMEs) still depend on contracts—a GDPR basis that is often overlooked due to its complexity. The contract’s lifecycle comprises many stages (e.g., drafting, negotiation, and signing) that must be executed in compliance with GDPR. Despite the active research efforts on digital contracts, contract-based GDPR compliance and challenges such as contract interoperability have not been sufficiently elaborated on yet. Since knowledge graphs and ontologies provide interoperability and support knowledge discovery, we propose and develop a knowledge graph-based tool for GDPR contract compliance verification (CCV). It binds GDPR’s legal basis to data sharing contracts. In addition, we conducted a performance evaluation in terms of execution time and test cases to validate CCV’s correctness in determining the overhead and applicability of the proposed tool in smart city and insurance application scenarios. The evaluation results and the correctness of the CCV tool demonstrate the tool’s practicability for deployment in the real world with minimum overhead.
Sai Sleghana Bala, Bhavya Prasad, Anjali Maruti Jadhav, Kumud Wasnik
This paper discusses how blockchain (Ethereum) can be used to as a solution to improve or mitigate communication and storage issues of healthcare information. Smart hospital functionality of drug tracing has been achieved using the non-replicable feature offered by non-fungible tokens (NFTs) generated by ERC721. Every manufacturer along with the medicines allotted to the distributer are treated as unique entities which cannot be replicated. All entity details are recorded in SQL databases. Registration of a patient with the insurance claim system, assigns a unique ID using Secure Hash Algorithm 256 (SHA256) improving security.
Jongho Seol, Jinfu Ke, Shital Joshi, N. Park · 5 authors
This paper proposes a quantitative model to assess the performance of a NFT (Non-Fungible Token)-centered chain as referred to as a NFT Chain in this paper. NFT chain in general stores its data distributed across on chain (e.g. NFT registration data and an address pointing at the data located off chain such as meta data table and ultimate digital asset's data) due to the high cost to store the potentially high volume of data for digital assets. Therefore, it is expected that the overall performance of NFT chain is primarily to be dominated and bound by the off-chain performance. The proposed performance model employing an embedded Markovian queueing process model, tracks a bivariate state of the NFT chain such that$(i,j)$where$i$stochastically tracks the number of slots of the transactions executed on chain and$j$stochastically tracks the number of transactions off chain as well, and the states transition as determined by$\lambda_{on}, \lambda_{off}, \mu$, and the number of slots in the current block. Extensive numerical simulations are performed to validate the efficacy of the model. The primary set of variables used in the simulations consists of$\lambda_{on}, \lambda_{off}, \mu$and the average number of slots of the transactions during a block posting,$L$, is simulated based on both$L_{on}$and$L_{off}$; and the average waiting time$W$based on both$W_{on}$and$W_{off}$, in an intermingled manner in order to take into account of the nature of NFT transactions executed across on- and off-chain without loss of generality. The simulation results demonstrate a good agreement with the expected and intuitive trends and the proposed NFT chain performance model serves as a sound theoretical foundation for the design of an NFT chain from the system's perspective.
Threats towards information systems have continued to increase and become more sophisticated, making security approaches a necessity for all types of organizations to ensure their protection. To implement an appropriate computer security policy, it is necessary to efficiently exploit the data that has become a valuable asset for these security systems, provided it is well used, controlled and monitored.In this paper, we focus on developing a decentralized solution based on Blockchain technology and IPFS (InterPlanetary File System) that can maintain and ensure the integrity of log files and sensitive information. The obtained results are promising, we obtained a distributed ledger of all log file transactions in a chronological sequence, which was shared among all Ethereum participants, allowing us to verify the log files' integrity, validity, and auditability throughout their life cycle.
Purpose This paper aims to provide a helpful tool for those who plan to implement blockchain-based solutions for the governance of the electronic medical record (EMR) in health-care settings. The goals are to identify each type of stakeholders involved in these projects and to clarify the relevance, to achieve success, of their readiness, intended as availability and ability to adopt blockchain. Design/methodology/approach The chosen methodology is a multiple case study on three initiatives that used blockchain to manage EMRs. This study relied on multiple sources of evidence. The primary data consisted of two rounds of semi-structured interviews with different informants. This study followed a grounded theory approach and performed within- and cross-case analyses. Findings This study identified the types of stakeholders – nodes and not-nodes – of the network and how their readiness level affects the implementation of blockchain-based projects applied to EMR. The nodes (e.g. patients and doctors) are pivotal in making the network working once this has been constructed. Out of the four readiness dimensions suggested by literature, motivational readiness, has the higher impact. Not-nodes stakeholders play a pivotal role in the project’s pre-implementation phase. For them, structural readiness is the dimension with the higher relevance. Originality/value To the best of the authors’ knowledge, it is the first time that a paper analyses the differences between nodes and not-nodes stakeholders of the blockchain network, in terms not only of type but also of readiness. Identifying the readiness level to implement successful projects is a fundamental step that has never been analysed in the health field.
Blockchain represents a trusted source of data for process mining where the benefit is mutual since process mining provides blockchain applications with helpful insights on user behavior, performance and security. However, blockchain data is not adequate for process mining and this issue has been studied in several works. The focus of existing works was on extracting event logs from activity-centric applications, excluding blockchain artifact-centric applications which are more common. To address this limitation, we propose an approach for extracting blockchain data from artifact-centric applications in a format that is suitable for process mining techniques. To do so, we introduce ACEL (Artifact-Centric Event Logs), an extension of the OCEL (Object-Centric Event Logs) standard for artifact-centric processes. We also propose an algorithm to extract ACEL logs from Ethereum, a blockchain platform. We implemented the approach and compared its results with related standards using as case study a popular Ethereum decentralized application.
Sandra Johnson, David Hyland-Wood, Anders L. Madsen, Kerrie Mengersen
The concept of 'Stateless Ethereum' was conceived with the primary aim of mitigating Ethereum's unbounded state growth. The key facilitator of Stateless Ethereum is through the introduction of 'witnesses' into the ecosystem. The changes and potential consequences that these additional data packets pose on the network need to be identified and analysed to ensure that the Ethereum ecosystem can continue operating securely and efficiently. In this paper we propose a Bayesian Network model, a probabilistic graphical modelling approach, to capture the key factors and their interactions in Ethereum mainnet, the public Ethereum blockchain, focussing on the changes being introduced by Stateless Ethereum to estimate the health of the resulting Ethereum ecosystem. We use a mixture of empirical data and expert knowledge, where data are unavailable, to quantify the model. Based on the data and expert knowledge available to use at the time of modelling, the Ethereum ecosystem is expected to remain healthy following the introduction of Stateless Ethereum.
Timotej Knez, Domen Gašperlin, Marko Bajec, Slavko Žitnik
Knowledge graphs are commonly represented by ontology-based databases. Tracking the provenance of ontological changes and ensuring ontology consistency is important. In this work, we propose a transaction manager for ontology-based database manipulation that combines blockchain and Semantic Web technologies. The latter is used for the efficient querying and modification of data, whereas the blockchain is used for the secure storage and tracking of changes. The blockchain enables a decentralized setup and data restoration. We evaluate our solution by measuring cost and time. Our solution introduces some overhead for updates whereas querying works at the same speed as the underlying ontology database.
Zusammenfassung In zunehmend vernetzten Systemen erstreckt sich die gesamte Datenwertschöpfungskette über eine Vielzahl an Systemen, wobei unterschiedliche Akteure mit unterschiedlichen und möglicherweise gegensätzlichen Interessen beteiligt sind. Es ist daher erforderlich, die Prozesse der Datenerfassung, Verarbeitung und Speicherung so abzusichern, dass Manipulationen durch externe Angriffe oder einzelne Akteure erkannt werden können. Dieser Beitrag legt den Fokus auf drei unterschiedliche technische Maßnahmen, durch welche Vertrauen in die ausgetauschten Daten selbst und letztendlich auch zwischen unterschiedlichen Akteuren hergestellt werden kann: Maßnahmen zur Kommunikationssicherheit schützen Daten während des Transports, digitale Kalibrierzertifikate erlauben eine Aussage über die Genauigkeit der erfassten Daten, Distributed-Ledger-Technologien wie zum Beispiel eine Blockchain erfassen Aktionen sowie beteiligte Akteure und legen diese Informationen manipulationsgeschützt ab. Dieser Beitrag bezieht sich auf das Forschungsprojekt GEMIMEG-II , das durch das Bundesministerium für Wirtschaft und Klimaschutz (BMWK) gefördert wird.
Abstract The Gaia-X project was initiated in 2019 by the German and French Ministers of Economy to ensure that companies would not lose control of their industrial data when it is hosted by non-EU cloud service providers. Since then, Gaia-X holds an international association presence in Belgium with more than 334 members, representing both users and providers across 20 countries and 16 national hubs and 5 candidate countries. The Association aims to increase the adoption of cloud services and accelerate data exchanges by European businesses through the facilitation of business data sovereignty with jointly approved (user and provider) policy rules on data portability and interoperability. Although for many enterprises, data sovereignty is seen as a prerequisite for using the cloud, a significant driver to boost the digital economy in business is incentivizing business data sharing. Two decades of cost optimization have constrained business value creation, driving many companies to neglect the opportunity to create shared value within a wider industry ecosystem. Now, thanks to the participation of large numbers of cloud users in the domains of Finance, Health, Energy, Automotive, Travel Aeronautics, Manufacturing, Agriculture, and Mobility, among others, Gaia-X is ideally positioned to help industries define appropriate data spaces and identify/develop compelling use cases, which can then be jointly deployed to a compliant-by-design platform architecture under the Gaia-X specifications, trust, and labeling frameworks. The creation of national Gaia-X hubs that act as independent think tanks, ambassadors, or influencers of the Association further facilitates the emergence of new data spaces and use/enabler cases at a country level, before these are subsequently extended to a European scope and beyond. Gaia-X partners share the view that data spaces will play a similar role in digital business as the web played 40 years ago to help the Internet take off. The Gaia-X Working Groups are at the core of the Gaia-X discussions and deliverables. There are three committees : the Technical, the Policies and Rules, and the Data Spaces and Business. The Technical Committee focus on key architectural elements and their evolution, such as and not limited to: Identity and Access Management: bridge the traditional X509 realm and new SSI realm, creating a decentralized network of identity federations Service Composition: how to assemble services in order to create new services with higher added value Self-Description : how to build digital trust at scale with measurable and comparable criteria The Policy and Rules Committee creates the deliverables required to develop the Gaia-X framework (compliance requirements, labels and qualification processes, credentials matrix, contractual agreements, etc.): The Labels and Qualification working group defines the E2E process for labels and qualification, from defining and evolving the levels of label, the process for defining new labels, and identifying and certifying existing CABS. The Credentials and Trust Anchors working group will develop and maintain a matrix of credentials and their verification methods to enable the implementation of compliance through automation, contractual clauses, certifications, or other methods. The Compliance working group collects compliance requirements from all sources to build a unique compliance requirements pool. The Data Spaces Business Committee helps the Association expanding and accelerating the creation of new Gaia-X service in the market: The Finance working group focuses on business modeling and supports the project office of the Association. The Technical working group analyzes the technical requirements from a business perspective. The Operational Requirements working group is the business requirements unit. The Hub working groups hold close contact with all Gaia-X Hubs and support the collection and creation of the Gaia-X use and business cases. These working groups maintain the international list of all use cases and data spaces and coordinate the Hubs.
The Ethereum Name Service (ENS) allows users to send and receive Ethereum as well as access special websites by using simple names rather than long, complex sequences of letters and numbers.