A Learner-Centred Approach for Lifelong Learning Powered by the Blockchain

The emergence of Blockchain technology promises to revolutionise not only the financial world, but also lifelong learning in many different ways. Blockchain technology offers opportunities to thoroughly rethink how we find educational content and training services online, how we register and pay for them, as well as how we get accredited for what we have learned and how this accreditation affects our career trajectory. This paper explores the different aspects of lifelong learning that are affected by this new paradigm and describes an ecosystem that places the learner at the centre of the learning process and its associated data. More specifically, we outline the ways that ePortfolios, accreditation and tutoring can evolve within this learner-centred ecosystem and we discuss the various benefits that this evolution bears for lifelong learners

Designing Incentives Enabled Decentralized User Data Sharing Framework

Data sharing practices are much needed to strike a balance between user privacy, user experience, and profit. Different parties collect user data, for example, companies offering apps, social networking sites, and others, whose primary motive is an enhanced business model while giving optimal services to the end-users. However, the collection of user data is associated with serious privacy and security issues. The sharing platform also needs an effective incentive mechanism to realize transparent access to the user data while distributing fair incentives. The emerging literature on the topic includes decentralized data sharing approaches. However, there has been no universal method to track who shared what, to whom, when, for what purpose and under what condition in a verifiable manner until recently, when the distributed ledger technologies emerged to become the most effective means for designing a decentralized peer-to-peer network. This Ph.D. research includes an engineering approach for specifying the operations for designing incentives and user-controlled data-sharing platforms. The thesis presents a series of empirical studies and proposes novel blockchains- and smart contracts-based DUDS (Decentralized User Data Sharing) framework conceptualizing user-controlled data sharing practices. The DUDS framework supports immutability, authenticity, enhanced security, trusted records and is a promising means to share user data in various domains, including among researchers, customer data in e-commerce, tourism applications, etc. The DUDS framework is evaluated via performance analyses and user studies. The extended Technology Acceptance Model and a Trust-Privacy-Security Model are used to evaluate the usability of the DUDS framework. The evaluation allows uncovering the role of different factors affecting user intention to adopt data-sharing platforms. The results of the evaluation point to guidelines and methods for embedding privacy, user transparency, control, and incentives from the start in the design of a data-sharing framework to provide a platform that users can trust to protect their data while allowing them to control it and share it in the ways they want

ArchCloudChain Dapp: the efficient workflow for interior designers

The interior design and construction industry involves various stakeholders who must collaborate and coordinate effectively to ensure the successful realization of projects. However, the existing workflow often suffers from fragmentation and inefficiency, leading to delays, errors, and increased costs. To address these challenges, this paper introduces the Arch Cloud Chain Dapp project, a decentralized software application that leverages blockchain technology and Building Information Modeling (BIM) to establish a transparent, secure, and efficient platform for stakeholder collaboration in interior design projects. The primary objective of this project is to reduce interior design costs while upholding high standards of quality and transparency. By integrating BIM and blockchain technology, the Arch Cloud Chain Dapp enables stakeholders to collaborate in real-time, significantly mitigating the risk of errors and miscommunication. Smart contracts play a crucial role in ensuring the enforceability and transparency of agreements, while the blockchain serves as an immutable ledger, providing an auditable record of all project transactions. These innovative features present a novel solution to the challenges faced by the interior design and construction industry. The Arch Cloud Chain Dapp project holds significant potential to revolutionize the industry by streamlining processes, enhancing collaboration, and reducing costs. Through its adoption, stakeholders can benefit from improved project outcomes, streamlined communication, and enhanced efficiency, ultimately leading to a more sustainable and prosperous interior design and construction sector

The future of social is personal: the potential of the personal data store

This chapter argues that technical architectures that facilitate the longitudinal, decentralised and individual-centric personal collection and curation of data will be an important, but partial, response to the pressing problem of the autonomy of the data subject, and the asymmetry of power between the subject and large scale service providers/data consumers. Towards framing the scope and role of such Personal Data Stores (PDSes), the legalistic notion of personal data is examined, and it is argued that a more inclusive, intuitive notion expresses more accurately what individuals require in order to preserve their autonomy in a data-driven world of large aggregators. Six challenges towards realising the PDS vision are set out: the requirement to store data for long periods; the difficulties of managing data for individuals; the need to reconsider the regulatory basis for third-party access to data; the need to comply with international data handling standards; the need to integrate privacy-enhancing technologies; and the need to future-proof data gathering against the evolution of social norms. The open experimental PDS platform INDX is introduced and described, as a means of beginning to address at least some of these six challenges

Taking Computation to Data: Integrating Privacy-preserving AI techniques and Blockchain Allowing Secure Analysis of Sensitive Data on Premise

PhD thesis in Information technologyWith the advancement of artificial intelligence (AI), digital pathology has seen significant progress in recent years. However, the use of medical AI raises concerns about patient data privacy. The CLARIFY project is a research project funded under the European Union’s Marie Sklodowska-Curie Actions (MSCA) program. The primary objective of CLARIFY is to create a reliable, automated digital diagnostic platform that utilizes cloud-based data algorithms and artificial intelligence to enable interpretation and diagnosis of wholeslide-images (WSI) from any location, maximizing the advantages of AI-based digital pathology. My research as an early stage researcher for the CLARIFY project centers on securing information systems using machine learning and access control techniques. To achieve this goal, I extensively researched privacy protection technologies such as federated learning, differential privacy, dataset distillation, and blockchain. These technologies have different priorities in terms of privacy, computational efficiency, and usability. Therefore, we designed a computing system that supports different levels of privacy security, based on the concept: taking computation to data. Our approach is based on two design principles. First, when external users need to access internal data, a robust access control mechanism must be established to limit unauthorized access. Second, it implies that raw data should be processed to ensure privacy and security. Specifically, we use smart contractbased access control and decentralized identity technology at the system security boundary to ensure the flexibility and immutability of verification. If the user’s raw data still cannot be directly accessed, we propose to use dataset distillation technology to filter out privacy, or use locally trained model as data agent. Our research focuses on improving the usability of these methods, and this thesis serves as a demonstration of current privacy-preserving and secure computing technologies

A Review of Blockchain Technology Based Techniques to Preserve Privacy and to Secure for Electronic Health Records

Research has been done to broaden the block chain’s use cases outside of finance since Bitcoin introduced it. One sector where block chain is anticipated to have a big influence is healthcare. Researchers and practitioners in health informatics constantly struggle to keep up with the advancement of this field's new but quickly expanding body of research. This paper provides a thorough analysis of recent studies looking into the application of block chain based technology within the healthcare sector. Electronic health records (EHRs) are becoming a crucial tool for health care practitioners in achieving these objectives and providing high-quality treatment. Technology and regulatory barriers, such as concerns about results and privacy issues, make it difficult to use these technologies. Despite the fact that a variety of efforts have been introduced to focus on the specific privacy and security needs of future applications with functional parameters, there is still a need for research into the application, security and privacy complexities, and requirements of block chain based healthcare applications, as well as possible security threats and countermeasures. The primary objective of this article is to determine how to safeguard electronic health records (EHRs) using block chain technology in healthcare applications. It discusses contemporary HyperLedgerfabrics techniques, Interplanar file storage systems with block chain capabilities, privacy preservation techniques for EHRs, and recommender systems