A blockchain is a form of distributed ledger technology where transactions as data state changes are permanently recorded securely and transparently without the need for third parties. Besides, introducing smart contracts to the blockchain has added programmability, revolutionizing the software ecosystem toward decentralized applications. Although promising, the usability of smart contracts is primarily limited to on-chain data without access to the external systems (i.e., off-chain) where real-world data and events reside. This connectability to off-chain data for smart contracts and blockchain is an open practical problem referred to as the “oracle problem” and is defined as how real-world data can be transferred into/from the blockchain. Hence, Blockchain oracles are introduced and implemented in the form of application programming interfaces connecting the real world to the blockchain for mitigating such a limitation. This article studies and analyzes how blockchain oracles provide final feedback (i.e., outcome) to smart contracts and survey blockchain oracle technologies and mechanisms regarding data integrity and correctness. Since the existing solutions are extensive in terms of characteristics and usage, we investigate their structure and principles by classifying the blockchain oracle implementation techniques into two major groups voting-based strategies and reputation-based ones. The former mainly relies on participants’ stakes for outcome finalization, while the latter considers reputation and performance metrics in conjunction with authenticity-proof mechanisms for data correctness and integrity. We present the result of this classification with a thorough discussion of the state of the art and provide the remaining challenges and future research directions in the end.

The Internet of Things (IoT) has enabled pervasive networking and multi-modal sensing, offering various services such as remote operations and augmenting existing processes. The military setting has increasingly and notably adopted IoT technologies, such as sensor-rich drones or autonomous vehicles, which provide military personnel with enhanced situational awareness, faster decision-making capabilities, and improved operational precision. However, integrating IoT into military systems introduces new security challenges due to increased connectivity and susceptibility to vulnerabilities. Cyberattacks on military IoT systems can have severe consequences, including operational disruptions and compromises of sensitive information. This article proposes a new perspective on examining threat models in IoT-enhanced combat systems, emphasising approaches for identifying threats, conducting vulnerability assessments, and suggesting countermeasures. It delves into the characteristics and structures of IoT-enhanced combat systems, exploring technical implementations and technologies. Additionally, it outlines five significant areas of focus, including blockchain, machine learning, game theory, protocols, and algorithms, to enhance understanding of IoT-enhanced combat systems. The insights gained from this analysis can inform the development of secure and resilient military IoT systems, ultimately enhancing the safety and effectiveness of military operations.

Digital twins, innovative virtual models synthesizing real-time biological, environmental, and lifestyle data, herald a new era in personalized medicine, particularly dermatology. These models, integrating medical-purpose Internet of Things (IoT) devices, deep and digital phenotyping, and advanced artificial intelligence (AI), offer unprecedented precision in simulating real-world physical conditions and health outcomes. Originating in aerospace and manufacturing for system behavior prediction, their application in healthcare signifies a paradigm shift towards patient-specific care pathways. In dermatology, digital twins promise enhanced diagnostic accuracy, optimized treatment plans, and improved patient monitoring by accommodating the unique complexities of skin conditions. However, a comprehensive review across PubMed, Embase, Web of Science, Cochrane, and Scopus until February 5th, 2024, underscores a significant research gap; no direct studies on digital twins’ application in dermatology is identified. This gap signals challenges, including the intricate nature of skin diseases, ethical and privacy concerns, and the necessity for specialized algorithms. Overcoming these barriers through interdisciplinary efforts and focused research is essential for realizing digital twins’ potential in dermatology. This study advocates for a proactive exploration of digital twins, emphasizing the need for a tailored approach to dermatological care that is as personalized as the patients themselves.

As a critical factor in ensuring the growth of the electronic auction (e-auction) domain, the privacy and security of the participants (sellers and buyers) must always be guaranteed. Traditionally, auction data, including participant details, are stored in a third party (auctioneer) database. This leads to a high risk of a single point of failure in terms of privacy and security. Toward this end, blockchain technology has emerged as a promising decentralized communication paradigm to address such risks. This paper presents a blockchain-based auction framework as a decentralized e-auctioning framework for location-aware services. In particular, the framework consists of three components: pre-auctioning, main auctioning, and post-auctioning processes with four algorithms. Our primary focus is on location-aware services, such as storage space rental, apartment rental, transport hire, and parking space rental. The trading volumes are expected to be high; hence, simplifying the design is a crucial requirement. In addition to the benefits of eliminating the centralized entity (the auctioneer), fees are redistributed among participants as rewards. Further, we incorporate a service quality monitoring method that ranks the services provided by participants. This ranking allows participants to determine the rank of other participants with whom they wish to trade. We have conducted several experiments to evaluate the proposed framework’s cost feasibility and to ensure the ease of the business flow.

In the United Arab Emirates, housing establishments offer citizens opportunities to apply for housing loans or grants. The eligibility for a loan or grant depends on the citizen’s income. Those with incomes below a predetermined threshold can apply for grants, while those with higher incomes are eligible for loans. Along with proof of income, other information such as the citizen’s health, fitness level, number of dependents, and marital status must be submitted with the application. This information, typically sourced from various government entities, must be verified. Traditionally, verifying this information through direct contact with these entities has been inefficient and time-consuming. To address this, we propose a blockchain-based, graph-traversing framework. This framework aims to create a secure mechanism for information sharing between housing establishments and government entities, thereby automating the processing of housing support applications. The framework also represents housing regulations as a graph, enabling updates to the regulations without disrupting workflow. We conducted several experiments to analyse the cost-effectiveness of the proposed framework, finding that processing a single application costs less than $1 on average.