Driven by the rapid progress in quantum hardware, recent years have witnessed a furious race for quantum technologies in both academia and industry. Universal quantum computers have supported up to hundreds of qubits, while the scale of quantum annealers has reached three orders of magnitude (i.e., thousands of qubits). Quantum computing power keeps climbing. Race has consequently generated an overwhelming number of research papers and documents. This article provides an entry point for interested readers to learn the key aspects of quantum computing and communications from a computer science perspective. It begins with a pedagogical introduction and then reviews the key milestones and recent advances in quantum computing. In this article, the key elements of a quantum Internet are categorized into four important issues, which are investigated in detail: a) quantum computers, b) quantum networks, c) quantum cryptography, and d) quantum machine learning. Finally, the article identifies and discusses the main barriers, the major research directions, and trends.

Despite artificial intelligence (AI)’s significant growth, its “black box” nature creates challenges in generating adequate trust. Thus, it is seldom utilized as a standalone unit in IoT high-risk applications, such as critical industrial infrastructures, medical systems, financial applications, etc. Explainable AI (XAI) has emerged to help with this problem. However, designing appropriately fast and accurate XAI is still challenging, especially in numerical applications. Here, we propose a universal XAI model, named the transparency relying upon statistical theory (TRUST), which is model-agnostic, high performing, and suitable for numerical applications. Simply put, TRUST XAI models the statistical behavior of the AI’s outputs in an AI-based system. Factor analysis is used to transform the input features into a new set of latent variables. We use mutual information (MI) to rank these variables and pick only the most influential ones on the AI’s outputs and call them “representatives” of the classes. Then, we use multimodal Gaussian (MMG) distributions to determine the likelihood of any new sample belonging to each class. We demonstrate the effectiveness of TRUST in a case study on cybersecurity of the Industrial Internet of Things (IIoT) using three different cybersecurity data sets. As IIoT is a prominent application that deals with numerical data. The results show that TRUST XAI provides explanations for new random samples with an average success rate of 98%. Compared with local interpretable model-agnostic explanations (LIME), a popular XAI model, TRUST is shown to be superior in the context of performance, speed, and the method of explainability. In the end, we also show how TRUST is explained to the user.

Blockchains have gained substantial attention from academia and industry for their ability to facilitate decentralized trust and communications. However, the rapid progress of quantum computing poses a significant threat to the security of existing blockchain technologies. Notably, the emergence of Shors and Grovers algorithms raises concerns regarding the compromise of the cryptographic systems underlying blockchains. Consequently, it is essential to develop methods that reinforce blockchain technology against quantum attacks. In response to this challenge, two distinct approaches have been proposed. The first approach involves post-quantum blockchains, which aim to utilize classical cryptographic algorithms resilient to quantum attacks. The second approach explores quantum blockchains, which leverage the power of quantum computers and networks to rebuild the foundations of blockchains. This paper aims to provide a comprehensive overview and comparison of post-quantum and quantum blockchains while exploring open questions and remaining challenges in these domains. It offers an in-depth introduction, examines differences in blockchain structure, security, privacy, and other key factors, and concludes by discussing current research trends.

FinTech has proven its true potential in traditional financial offerings by delivering digital financial services to individuals worldwide. The pandemic has accelerated how people interact with financial services and has resulted in long-term changes to societies and economies. FinTech has expanded access to financial services and has made such changes possible. FinTech or Financial Technology refers to using new technologies for financial services. Artificial Intelligence, Blockchain, and cloud computing are a few technologies currently being applied to FinTech. In this paper, we consider FinTech, which partly uses blockchain technology. Blockchain technology plays a vital role in the financial sector as it ultimately lifts trust and the need for third-party verification by using consensus-based verification. This survey provides a comprehensive summary of the most relevant blockchain-based FinTech implementations and an overview of FinTech sectors and segments. For each segment, we provide a critique and a discussion on how each blockchain implementation contributes to solving the majority of problems faced by FinTech companies and researchers. This research aims to direct the future of financial solutions by providing an outline of the applications of blockchain technology and distributed ledger technology (DLT) for FinTech. We discuss various implementations, limitations, and challenges of blockchain-based FinTech applications. We conclude this work by exploring possible strengths, weaknesses, opportunities, and threats (SWOT) analysis and future research directions.

Blockchain technology has been prominent recently due to its applications in cryptocurrency. Numerous decentralized blockchain applications have been possible due to blockchains’ nature of distributed, secured, and peer-to-peer storage. One of its technical pillars is using public-key cryptography and hash functions, which promise a secure, pseudoanonymous, and distributed storage with nonrepudiation. This security is believed to be difficult to break with classical computational powers. However, recent advances in quantum computing have raised the possibility of breaking these algorithms with quantum computers, thus, threatening the blockchains’ security. Quantum-resistant blockchains are being proposed as alternatives to resolve this issue. Some propose to replace traditional cryptography with postquantum cryptography—others base their approaches on quantum computer networks or quantum internets. Nonetheless, a new security infrastructure (e.g., access control/authentication) must be established before any of these could happen. This article provides a theoretical analysis of the quantum blockchain technologies that could be used for decentralized identity authentication. We put together a conceptual design for a quantum blockchain identity framework and give a review of the technical evidence. We investigate its essential components and feasibility, effectiveness, and limitations. Even though it currently has various limitations and challenges, we believe a decentralized perspective of quantum applications is noteworthy and likely.

With the emergence of the Quantum Internet, the need for advanced quantum networking techniques has significantly risen. Various models of quantum repeaters have been presented, each delineating a unique strategy to ensure quantum communication over long distances. We focus on repeaters that employ entanglement generation and swapping. This revolves around establishing remote end-to-end entanglement through repeaters, a concept we denote as the “quantum-native” repeaters (also called “first-generation” repeaters in some literature). The challenges in routing with quantum-native repeaters arise from probabilistic entanglement generation and restricted coherence time. Current approaches use synchronized time slots to search for entanglement-swapping paths, resulting in inefficiencies. Here, we propose a new set of asynchronous routing protocols for quantum networks by incorporating the idea of maintaining a dynamic topology in a distributed manner, which has been extensively studied in classical routing for lossy networks, such as using a destination-oriented directed acyclic graph or a spanning tree. The protocols update the entanglement-link topology asynchronously, identify optimal entanglement-swapping paths, and preserve unused direct-link entanglements. Our results indicate that asynchronous protocols achieve a larger upper bound with an appropriate setting and significantly higher entanglement rate than existing synchronous approaches, and the rate increases with coherence time, suggesting that it will have a much more profound impact on quantum networks as technology advances.