This work addresses the issues involved in providing robust certification for COVID-19 immunity (assuming the biological premise of 'immunity' is ultimately confirmed). Methods: We developed a prototype mobile phone app and scalable distributed server architecture that facilitates instant verification of tamper-proof test results. Personally identifiable information is only stored at the user's discretion, and the app allows the end-user selectively to present only the specific test result with no other personal information revealed. Behind the scenes it relies upon (a) the 2019 World Wide Web Consortium standard called 'Verifiable Credentials', (b) Tim Berners-Lee's decentralized personal data platform 'Solid', and (c) a consortium Ethereum-based blockchain. Results: Our architecture enables verifiability and privacy in a manner derived from public/private key pairs and digital signatures, generalized to avoid restrictive ownership of sensitive digital keys and/or data. Benchmark performance tests show it to scale linearly in the worst case, as significant processing is done locally on each app. For the test certificate Holder, Issuer (e.g. doctor, pharmacy) and Verifier (e.g. employer), it is 'just another app' which takes only minutes to use. Conclusions: The app and distributed server architecture offer a prototype proof of concept that is readily scalable, widely applicable to personal health records and beyond, and in effect 'waiting in the wings' for the biological issues, plus key ethical issues raised in the discussion section, to be resolved.
Distributed Ledger Technology (DLT) has emerged as one of the most disruptive technologies in the last decade. It promises to change the way people do their business, track their products, and manage their personal data. Though the concept of DLT was first implemented in 2009 as Bitcoin, it has gained significant attention only in the past few years. During this time, different DLT enthusiasts and commercial companies have proposed and developed several DLT platforms. These platforms are usually categorized as public vs private, general purpose vs application specific and so on. As a growing number of people are interested to build DLT applications, it is important to understand their underlying architecture and capabilities in order to determine which DLT platform should be leveraged for a specific DLT application. In addition, the platforms need to be evaluated and critically analyzed to assess their applicability, resiliency and sustainability in the long run. In this paper, we have surveyed several leading DLT platforms and evaluated their capabilities based on a number of quantitative and qualitative criteria. The comparative analysis presented in this paper will help the DLT developers and architects to choose the best platform as per their requirement(s). INDEX TERMS Distributed ledger technology, blockchain, immutability, DLT platforms.
Contact tracing has become a vital tool for public health officials to effectively combat the spread of new diseases, such as the novel coronavirus disease COVID-19. Contact tracing is not new to epidemiologist rather, it used manual or semi-manual approaches that are incredibly time-consuming, costly and inefficient. It mostly relies on human memory while scalability is a significant challenge in tackling pandemics. The unprecedented health and socio-economic impacts led researchers and practitioners around the world to search for technology-based approaches for providing scalable and timely answers. Smartphones and associated digital technologies have the potential to provide a better approach due to their high level of penetration, coupled with mobility. While data-driven solutions are extremely powerful, the fear among citizens is that information like location or proximity associated with other personal data can be weaponised by the states to enforce surveillance. Low adoption rate of such apps due to the lack of trust questioned the efficacy and demanded researchers to find innovative solution for building digital-trust, and appropriately balancing privacy and accuracy of data. In this paper, we have critically reviewed such protocols and apps to identify the strength and weakness of each approach. Finally, we have penned down our recommendations to make the future contact tracing mechanisms more universally inter-operable and privacy-preserving.
The Internet of Things (IoT) is experiencing an exponential growth in a wide variety of usecases in multiple application domains, such as healthcare, agriculture, smart cities, smart homes, supply chain and so on. To harness its full potential, it must be based upon a resilient network architecture with strong support for security, privacy and trust. Most of these issues still remain to be addressed carefully for the IoT systems. Blockchain technology has recently emerged as a breakthrough technology with the potential to deliver some valuable properties such as resiliency, support for integrity, anonymity, decentralisation and autonomous control. A number of blockchain platforms are proposed that may be suitable for di erent use-cases including IoT applications. In such, the possibility to integrate the IoT and blockchain technology is seen as a potential solution to address some crucial issues. However, to achieve this, there must be a clear understanding of the requirements of di erent IoT applications and the suitability of a blockchain platform for a particular application satisfying its underlying requirements. This chapter aims to achieve this goal by describing an evaluation framework which can be utilised to select a suitable blockchain platform for a given IoT application.
Contact tracing has become a vital tool for public health officials to effectively combat the spread of new diseases, such asthe novel coronavirus disease COVID-19. Contact tracing is not new to epidemiologist rather, it used manual or semi-manualapproaches that are incredibly time-consuming, costly and inefficient. It mostly relies on human memory while scalabilityis a significant challenge in tackling pandemics. The unprecedented health and socio-economic impacts led researchersand practitioners around the world to search for technology-based approaches for providing scalable and timely answers.Smartphones and associated digital technologies have the potential to provide a better approach due to their high level ofpenetration, coupled with mobility. While data-driven solutions are extremely powerful, the fear among citizens is thatinformation like location or proximity associated with other personal data and can be weaponised by the states to enforcesurveillance. Low adoption rate of such apps due to the lack of trust questioned the efficacy and demanded researchers tofind innovative solution for building digital-trust, and appropriately balancing privacy and accuracy of data. In this paper,we have critically reviewed such protocols and apps to identify the strength and weakness of each approach. Finally, wehave penned down our recommendations to make the future contact tracing mechanisms more universally inter-operable andprivacy-preserving.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.