Decentralized Identity for Industrial Applications

This thesis looks at some aspects of current authorization to applications, then explores new ways of solving this with emerging technology originated from the ever expanding field of blockchain. This accumulates to an architecture that could work for organizations that want to work together. This architecture is tried im- plemented, then drafts the outcome of the process

A Distributed Trust Framework for Privacy-Preserving Machine Learning

When training a machine learning model, it is standard procedure for the researcher to have full knowledge of both the data and model. However, this engenders a lack of trust between data owners and data scientists. Data owners are justifiably reluctant to relinquish control of private information to third parties. Privacy-preserving techniques distribute computation in order to ensure that data remains in the control of the owner while learning takes place. However, architectures distributed amongst multiple agents introduce an entirely new set of security and trust complications. These include data poisoning and model theft. This paper outlines a distributed infrastructure which is used to facilitate peer-to-peer trust between distributed agents; collaboratively performing a privacy-preserving workflow. Our outlined prototype sets industry gatekeepers and governance bodies as credential issuers. Before participating in the distributed learning workflow, malicious actors must first negotiate valid credentials. We detail a proof of concept using Hyperledger Aries, Decentralised Identifiers (DIDs) and Verifiable Credentials (VCs) to establish a distributed trust architecture during a privacy-preserving machine learning experiment. Specifically, we utilise secure and authenticated DID communication channels in order to facilitate a federated learning workflow related to mental health care data.Comment: To be published in the proceedings of the 17th International Conference on Trust, Privacy and Security in Digital Business - TrustBus202

Enabling discoverable trusted services for highly dynamic decentralized workflows

Fifth generation (5G) mobile networks will revolutionize edge-based computing by providing fast and reliable network capabilities to remote sensors, devices and microservices. This heralds new opportunities for researchers, allowing remote instrumentation and analytic capabilities to be as accessible as local resources. The increased availability of remote data and services presents new opportunities for collaboration, yet introduces challenges for workflow orchestration, which will need to adapt to consider an increased choice of available services, including those from trusted partners and the wider community. In this paper we outline a workflow approach that provides decentralized discovery and orchestration of verifiably trustable services in support of multi-party operations. We base this work on the adoption of standardised data models and protocols emerging from hypermedia research, which has demonstrated success in using combinations of Linked Data, Web of Things (WoT) and semantic technologies to provide mechanisms for autonomous goal-directed agents to discover, execute and reuse new heterogeneous resources and behaviours in large-scale, dynamic environments. We adopt Verifiable Credentials (VCs) to securely share information amongst peers based on prior service usage in a cryptographically secure and tamperproof way, providing a trust-based framework for ratifying service qualities. Collating these new service description channels and integrating with existing decentralized workflow research based on vector symbolic architecture (VSA) provides an enhanced semantic search space for efficient and trusted service discovery that will be necessary for 5G edge-computing environments

Self-Sovereign Identity Ecosystems: Benefits and Challenges

Verifiable credentials, coupled with decentralized ledger technologies, have been potential providers of trustworthy digital identity for individuals, organizations, and other entities, and thus, potential enablers of trustful digital interactions. The rapid development of this technology—called self-sovereign identity (SSI)—and the ecosystems built around it have been fostered even more by the societal needs stemming from the current pandemic crisis, when governments, non-profit organizations, businesses, and individuals are working together on different aspects of SSI to enable mainstream adoption. In this study, we build on rich qualitative data gathered from SSI practitioners to give a fresh overview of the perceived benefits and challenges of SSI. The paper advances research on the domain of SSI adoption and provides valuable insights into the feasibility of SSI for practitioners both in the private and public sectors

Trustchain -- Trustworthy Decentralised Public Key Infrastructure for Digital Credentials

The sharing of public key information is central to the digital credential security model, but the existing Web PKI with its opaque Certification Authorities and synthetic attestations serves a very different purpose. We propose a new approach to decentralised public key infrastructure, designed for digital identity, in which connections between legal entities that are represented digitally correspond to genuine, pre-existing relationships between recognisable institutions. In this scenario, users can judge for themselves the level of trust they are willing to place in a given chain of attestations. Our proposal includes a novel mechanism for establishing a root of trust in a decentralised setting via independently-verifiable timestamping. We also present a reference implementation built on open networks, protocols and standards. The system has minimal setup costs and is freely available for any community to adopt as a digital public good.Comment: 10 pages, 4 figures, presented at the International Conference on AI and the Digital Economy (CADE 2023), Venice, Italy. Replaces the preprint version, with minor changes & additions based on reviewers' comment

Towards a Modelling Framework for Self-Sovereign Identity Systems

Self-sovereign Identity promises to give users control of their own data, and has the potential to foster advancements in terms of personal data privacy. Self-sovereign concepts can also be applied to other entities, such as datasets and devices. Systems adopting this paradigm will be decentralised, with messages passing between multiple actors, both human and representing other entities, in order to issue and request credentials necessary to meet individual and collective goals. Such systems are complex, and build upon social and technical interactions and behaviours. Modelling self-sovereign identity systems seeks to provide stakeholders and software architects with tools to enable them to communicate effectively, and lead to effective and well-regarded system designs and implementations. This paper draws upon research from Actor-based Modelling to guide a way forward in modelling self-sovereign systems, and reports early success in utilising the iStar 2.0 framework to provide a representation of a birth registration case study

Blockchain for Genomics:A Systematic Literature Review

Human genomic data carry unique information about an individual and offer unprecedented opportunities for healthcare. The clinical interpretations derived from large genomic datasets can greatly improve healthcare and pave the way for personalized medicine. Sharing genomic datasets, however, pose major challenges, as genomic data is different from traditional medical data, indirectly revealing information about descendants and relatives of the data owner and carrying valid information even after the owner passes away. Therefore, stringent data ownership and control measures are required when dealing with genomic data. In order to provide secure and accountable infrastructure, blockchain technologies offer a promising alternative to traditional distributed systems. Indeed, the research on blockchain-based infrastructures tailored to genomics is on the rise. However, there is a lack of a comprehensive literature review that summarizes the current state-of-the-art methods in the applications of blockchain in genomics. In this paper, we systematically look at the existing work both commercial and academic, and discuss the major opportunities and challenges. Our study is driven by five research questions that we aim to answer in our review. We also present our projections of future research directions which we hope the researchers interested in the area can benefit from

Blockchain for Genomics:A Systematic Literature Review

Human genomic data carry unique information about an individual and offer unprecedented opportunities for healthcare. The clinical interpretations derived from large genomic datasets can greatly improve healthcare and pave the way for personalized medicine. Sharing genomic datasets, however, pose major challenges, as genomic data is different from traditional medical data, indirectly revealing information about descendants and relatives of the data owner and carrying valid information even after the owner passes away. Therefore, stringent data ownership and control measures are required when dealing with genomic data. In order to provide secure and accountable infrastructure, blockchain technologies offer a promising alternative to traditional distributed systems. Indeed, the research on blockchain-based infrastructures tailored to genomics is on the rise. However, there is a lack of a comprehensive literature review that summarizes the current state-of-the-art methods in the applications of blockchain in genomics. In this paper, we systematically look at the existing work both commercial and academic, and discuss the major opportunities and challenges. Our study is driven by five research questions that we aim to answer in our review. We also present our projections of future research directions which we hope the researchers interested in the area can benefit from