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Blockchains-based smart contracts are disrupting the smart real estate sector of the smart cities. The current study explores the literature focused on blockchain smart contracts in smart real estate and proposes a conceptual framework for its adoption in smart cities. Based on a systematic review method, the literature published between 2000 and 2020 is explored and analyzed. From the literature, ten key aspects of the blockchain smart contracts are highlighted that are grouped into six layers for adopting the smart contracts in smart real estate. The decentralized application and its interactions with Ethereum Virtual Machine (EVM) are presented to show the development of a smart contract that can be used for blockchain smart contracts in real estate. Further, a detailed design and interaction mechanism are highlighted for the real estate owners and users as parties to a smart contract. A list of functions for initiating, creating, modifying, or terminating a smart contract is presented along with a stepwise procedure for establishing and terminating smart contracts. The current study can help the users enjoy a more immersive, user-friendly, and visualized contracting process, whereas the owners, property technologies (Proptech) companies, and real estate agents can enjoy more business and sales. This can help disrupt traditional real estate and transform it into smart real estate in line with industry 4.0 requirements.

The aim of our systematic review was to inspect the recently published literature on decentralized governance systems and integrate the insights it articulates on blockchain technology and smart contracts by employing Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Throughout January and May 2022, a quantitative literature review of ProQuest, Scopus, and the Web of Science databases was carried out, with search terms including \"city\" + \"blockchain technology\", \"smart contracts\", and \"decentralized governance systems\". As the analyzed research studies were published between 2016 and 2022, only 371 sources satisfied the eligibility criteria. A Shiny app was harnessed for the PRISMA flow diagram to include evidence-based acquired and handled data. Analyzing the most recent and relevant sources and leveraging screening and quality assessment tools such as AMSTAR, Dedoose, Distiller SR, ROBIS, and SRDR, we integrated the core outcomes and robust correlations related to smart urban governance. As data visualization tools, for initial bibliometric mapping dimensions were harnessed, together with layout algorithms provided by VOSviewer. Future research should investigate smart contract governance of blockchain applications and infrastructure using decision-making tools and spatial cognition algorithms.

In this paper, we propose a smart contract broker to improve the reusability of smart contracts in a blockchain environment. The current blockchain platform lacks a standard approach to sharing and managing smart contracts, which makes it difficult for developers to reuse them and leads to efficiency issues. The proposed smart contract broker uses tags to identify and organize smart contracts, and it provides an environment for comparing and reusing smart contracts. This improves the reusability of smart contracts and efficiency. The proposed smart contract broker can be applied as a reference model that increases the flexibility and reusability of smart contract management in a blockchain environment.

The general public is becoming increasingly familiar with blockchain technology. Numerous new applications are made possible by this technology's unique features, which include transparency, strong security via cryptography, and distribution. These applications need certain programming tools and interfaces to be implemented. This is made feasible by smart contracts. If the prerequisites are satisfied, smart contracts are carried out automatically. Any mistake in smart contract coding, particularly security-related ones, might have an impact on the project as a whole, available funds, and important data. The current paper discusses the flaws of the Ethereum smart contract in this respect. By examining publically accessible scientific sources, this work aims to present thorough information about vulnerabilities, examples, and current security solutions. Additionally, a substantial collection of current Ethereum (ETH) smart contracts has undergone a static code examination to conduct the vulnerability-finding procedure. The output has undergone assessments and statistical analysis. The study's conclusions demonstrate that smart contracts have several distinct flaws, including arithmetic flaws, that developers should be more aware of. These vulnerabilities and the solutions that can be used to address them are also included.

A massive amount of sensitive personal data is being collected and used by scientists, businesses, and governments. This has led to unprecedented threats to privacy rights and the security of personal data. There are few solutions that empower individuals to provide systematic consent agreements on distinct personal information and control who can collect, access, and use their data for specific purposes and periods. Individuals should be able to delegate consent rights, access consent-related information, and withdraw their given consent at any time. We propose a smart-contract-based dynamic consent management system, backed by blockchain technology, targeting personal data usage under the general data protection regulation. Our user-centric dynamic consent management system allows users to control their personal data collection and consent to its usage throughout the data lifecycle. Transaction history and logs are recorded in a blockchain that provides trusted tamper-proof data provenance, accountability, and traceability. A prototype of our system was designed and implemented to demonstrate its feasibility. The acceptability and reliability of the system were assessed by experimental testing and validation processes. We also analyzed the security and privacy of the system and evaluated its performance.

The vehicle drivers pose a huge problem in determining an optimal parking space as the density of vehicles in big cities have rapidly increased over the recent years. This objective of drivers towards the identification of parking availability causes traffic congestion, time wastage and air toxicity. At this juncture, the smart parking systems enable the drivers to reserve parking spaces and achieve real time parking information. But, most of state-of-the art smart parking solutions call for requiring drivers to disclose potentially sensitive information, such as their intended destination. In addition, the chances of single point failure are maximized as the available due to their total centralization smart parking solutions are quite susceptible to privacy invasions by the service providers. In this paper, Efficiency of a Smart Parking System in Privacy-Preserving using Multi Transaction Mode Consortium blockchain. This private information retrieval scheme is proposed with the benefits of enhanced multi-transaction mode consortium blockchain which is built by various parking lot proprietors for maximizing parking offers through the inclusive factors of accessibility, openness, and security. It is proposed to covertly retrieve parking offers from the improved multi-transaction mode consortium blockchain in order to protect drivers’ location privacy. It also included the merits of light-weighted quantum blind signature for guaranteeing the drivers with a significant anonymous authentication process that aids in determining the feasibility and available parking slot reservation. The results confirmed the predominance of the proposed private information retrieval scheme with respect to the maximized privacy preservation of drivers’ sensitive information with minimized communication and computation overheads.

Blockchain technology can drastically reduce the costs associated with claim verification in the insurance and Takaful industry while increasing trust among involved parties through smart contracts and a shared source of truth. This study examines whether Takaful operators and insurance companies apply blockchain differently and explores the benefits of blockchain technology and smart contracts for both. It conducts a systematic review of relevant literature and a meta-analysis to assess how current studies describe and combine cases as evidence. The results indicate that Takaful and insurance companies that use smart contracts experience a reduction in fraudulent claims, increased transparency, enhanced connections between involved parties, and automation of claim payments with minimal human intervention. The analysis reveals no difference in the application of blockchain technology between the two types of operators, despite the distinct operating contracts of Takaful and conventional insurance.

In order to solve the problem of data security and management between IoT edge nodes and massive heterogeneous devices, combined with the wide application of blockchain technology in distributed system data security management, a blockchain-based Internet of Things access control model (SC-ABAC) is proposed by combining smart contracts and attribute-based access control. The traditional consensus algorithm PoW (Proof of Work) and SC-ABAC access control management process are optimized. By quantitative analysis, the time to call contracts in the query process increases linearly, the time of the policy addition and judgment process is constant, and the energy consumption of the optimized consensus mechanism is smaller than that of the PoW unit. This model provides decentralized, fine-grained, and dynamic access control management in IoT environments, enabling distributed systems to reach consensus faster and ensure data consistency.

Artificial intelligence (AI) and machine learning (ML) have become integral to various applications, leveraging vast amounts of heterogeneous, globally distributed Internet of Things (IoT) data to identify patterns and build accurate ML models for predictive tasks. Federated learning (FL) is a distributed ML technique developed to learn from such distributed data while ensuring privacy. Nevertheless, traditional FL requires a central server for aggregation, which can be a central point of failure and raises trust issues. Blockchain-based federated learning (BFL) has emerged as an FL extension that provides guaranteed decentralization alongside other security assurances. However, due to the inherent openness of blockchain, BFL comes with several vulnerabilities that remain unexplored in literature, e.g., a higher possibility of model poisoning attacks. This paper investigates how scaling-based model poisoning attacks are made easier in BFL systems and their effects on model performance. Subsequently, it proposes FedECPA-an extension of FedAvg aggregation algorithm with Efficient Countermeasure against scaling-based model Poisoning Attacks in BFL. FedECPA filters out clients with outlier weights and protects the model against these attacks. Several experiments are conducted with different attack scenarios and settings. We further compared our results to a frequently used defense mechanism, Multikrum. Results show the effectiveness of our defense mechanism in protecting BFL from these attacks. On the MNIST dataset, it maintains an overall accuracy of 98% and 89% and outperforms our baseline with 4% and 38% in both IID and non-IID settings, respectively. Similar results were achieved with the CIFAR-10 dataset.

Supply chain finance (SCF) provides credit for small and medium-sized enterprises with low credit lines and small financing scales. The resulting financial credit data and related business transaction data are highly confidential and private. However, traditional SCF management schemes use third-party platforms and centralized designs that cannot achieve highly reliable secure storage and fine-grained access control. To address such a need, we propose Fabric-SCF, designing and implementing a Blockchain-based secure storage system by utilizing distributed consensus to realize data security, traceability, and immutability. The attribute-based access control model is deployed for access control, also utilizing smart contracts to define system processes and access policies to ensure the system’s efficient operation. To verify the performance of Fabric-SCF, two sets of simulation experiments are designed its effectiveness. Experimental results show that Fabric-SCF achieves dynamic and fine-grained access control while maintaining high throughput in a simulated real-world operating scenario.