The blockchain is an emerging technology which has the potential to improve many information systems. In this regard, the applications and the platform they are built on must be able to connect and communicate with each other. However, the current blockchain platforms have several limitations, such as lack of interoperability among different systems. The existing platforms of blockchain applications operate only within their own networks. Even though the underlying technology is similar, it relies on centralized third-party mediators to exchange or retrieve information from other blockchain networks. The current third-party intermediaries establish trust and security by preserving a centralized ledger to track ‘account balances’ and vouch for a transaction’s authenticity. The inability for independent blockchains to communicate with one another is an inherent problem in the decentralized systems. Lack of appropriate inter-blockchain communication puts a strain on the mainstream adoption of blockchain. It is evident that blockchain technology has the potential to become a suitable solution for some systems if it can scale and is able to cross communicate with other systems. For the multisystem blockchain concept to become a reality, a mechanism is required that would connect and communicate with multiple entities’ blockchain systems in a distributed fashion (without any intermediary), while maintaining the property of trust and integrity built by individual blockchains. In this article, we propose a mechanism that provides cross-chain interoperability using transactions.

Artificial intelligence (AI) encompasses the development of systems that perform tasks typically requiring human intelligence, such as reasoning and learning. Despite its widespread use, AI often raises trust issues due to the opacity of its decision-making processes. This challenge has led to the development of explainable artificial intelligence (XAI), which aims to enhance user understanding and trust by providing clear explanations of AI decisions and processes. This paper reviews existing XAI research, focusing on its application in the healthcare sector, particularly in medical and medicinal contexts. Our analysis is organized around key properties of XAI—understandability, comprehensibility, transparency, interpretability, and explainability—providing a comprehensive overview of XAI techniques and their practical implications.

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.

Interoperability is identified as one of the major design constraints for blockchain technology. Cross-blockchain technology is fast evolving as the demand for value transfer among different blockchain systems is growing. A generic cross-blockchain design methodology for interoperability requires a set of suitable components to facilitate the integration process. One of the main challenges in the integration is to protect the integrity of the shared data. Various integration systems and their components may operate with different underlying security assumptions and this may lead to compromise of the overall security. In this paper we review the latest advancement in blockchain integration systems and provide a comprehensive analysis of integration characteristics for cross-blockchain technology and then define the essential components and modes of integration. Based on the outcome of our review, we propose a novel integration design decision framework that identifies key assumptions and critical characteristics of the cross-blockchain technology. The proposed framework facilitates the best-practice decision-making process. This reduces the potential for design errors and the associated security risks and performance degradation of the overall system.