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The most important and difficult challenge the digital society has recently faced is ensuring data privacy and security in cloud‐based Internet of Things (IoT) technologies. As a result, many researchers believe that the blockchain's Distributed Ledger Technology (DLT) is a good choice for various clever applications. Nevertheless, it encountered constraints and difficulties with elevated computing expenses, temporal demands, operational intricacy, and diminished security. Therefore, the proposed work aims to develop a Decentralized Identifiable Distributed Ledger Technology‐Blockchain (DIDLT‐BC) framework that is intelligent and effective, requiring the least amount of computing complexity to ensure cloud IoT system safety. In this case, the Rabin algorithm produces the digital signature needed to start the transaction. The public and private keys are then created to verify the transactions. The block is then built using the DIDLT model, which includes the block header information, hash code, timestamp, nonce message, and transaction list. The primary purpose of the Blockchain Consent Algorithm (BCA) is to find solutions for numerous unreliable nodes with varying hash values. The novel contribution of this work is to incorporate the operations of Rabin digital data signature generation, DIDLT‐based blockchain construction, and BCA algorithms for ensuring overall data security in IoT networks. With proper digital signature generation, key generation, blockchain construction and validation operations, secured data storage and retrieval are enabled in the cloud‐IoT systems. By using this integrated DIDLT‐BCA model, the security performance of the proposed system is greatly improved with 98% security, less execution time of up to 150 ms, and reduced mining time of up to 0.98 s. [ABSTRACT FROM AUTHOR]

License Plate Recognition (LPR) is essential for the Internet of Vehicles (IoV) since license plates are a necessary characteristic for distinguishing vehicles for traffic management. As the number of vehicles on the road continues to grow, managing and controlling traffic has become increasingly complex. Large cities in particular face significant challenges, including concerns around privacy and the consumption of resources. To address these issues, the development of automatic LPR technology within the IoV has emerged as a critical area of research. By detecting and recognizing license plates on roadways, LPR can significantly enhance management and control of the transportation system. However, implementing LPR within automated transportation systems requires careful consideration of privacy and trust issues, particularly in relation to the collection and use of sensitive data. This study recommends a blockchain-based approach for IoV privacy security that makes use of LPR. A system handles the registration of a user's license plate directly on the blockchain, avoiding the gateway. The database controller may crash as the number of vehicles in the system rises. This paper proposes a privacy protection system for the IoV using license plate recognition based on blockchain. When a license plate is captured by the LPR system, the captured image is sent to the gateway responsible for managing all communications. When the user requires the license plate, the registration is done by a system connected directly to the blockchain, without going through the gateway. Moreover, in the traditional IoV system, the central authority has full authority to manage the binding of vehicle identity and public key. As the number of vehicles increases in the system, it may cause the central server to crash. Key revocation is the process in which the blockchain system analyses the behaviour of vehicles to judge malicious users and revoke their public keys. [ABSTRACT FROM AUTHOR]

The advancement of hardware, software, and Internet infrastructure leads to the increasing quantities of smart Internet of Things (IoT) devices. Meanwhile, security issues have increasingly brought to us the concerns due to the evolving IoT scope and mass communications. Trusting service vendors depends on their devices that generate information and provide executions. Blockchain becomes an attractive choice, as evidenced by its wide adoptions. However, trusting IoT-based services becomes an important issue since the implementation of Blockchain-based IoT (BIoT) services is proprietary and independent. This paper introduces a generic architecture design that incorporates Public Key Infrastructure (PKI) to establish trust of BIoT services. This can potentially solve the trust problem and based on our experiment it can be scaled well. We also demonstrate how specification languages can be useful to express requirements. It decouples users from Blockchain and thus they can specify qualities of BIoT services without deep knowledge to work with Blockchain. [ABSTRACT FROM AUTHOR]

Due to energy efficiency and near real-time finality settlement, permissioned blockchain is mainly used in blockchain-based Internet of Things (BIoT) services. This blockchain requires validators to reach the consensuses. Currently, the validators are chosen based on generic attributes of trusted nodes capriciously. However, service users have no mechanism to provide their requirements in assessing validators. Existing works are biased from users’ perspectives, which risks collusion attacks due to improperly selected validators. This article aims to solve this by considering users’ expectations on services. A user-oriented framework is proposed to evaluate the trust of BIoT services with the consideration of validator attributes. It provides an effective mechanism to express requirements. Specification language is adopted in our algorithm to perform compliance checking. The feasibility has been verified in a simulation. We found that the permissioned blockchain has also benefited from the proposed user-oriented selection of validators in terms of computing efficiency due to additional constraints. [ABSTRACT FROM AUTHOR]

Business process management (BPM) aims to optimize business processes to achieve better system performance such as higher profit, quicker response, and better services. BPM systems in Industry 4.0 are required to digitize and automate business process workflows and support the transparent interoperations of service vendors. The critical bottleneck to advance BPM systems is the evaluation, verification, and transformation of trustworthiness and digitized assets. Most of BPM systems rely heavily on domain experts or third parties to deal with trustworthiness. In this paper, an automated BPM solution is investigated to select and compose services in open business environment, Blockchain technology (BCT) is explored and proposed to transfer and verify the trustiness of businesses and partners, and a BPM framework is developed to illustrate how BCT can be integrated to support prompt, reliable, and cost-effective evaluation and transferring of Quality of Services in the workflow composition and management. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) technology in various applications used in data processing systems requires high security because more data must be saved in cloud monitoring systems. Even though numerous procedures are in place to increase the security and dependability of data in IoT applications, the majority of outside users can decode any transferred data at any time. Therefore, it is essential to include data blocks that, under any circumstance, other external users cannot understand. The major significance of proposed method is to incorporate an offloading technique for data processing that is carried out by using block chain technique where complete security is assured for each data. Since a problem methodology is designed with respect to clusters a load balancing technique is incorporated with data weights where parametric evaluations are made in real time to determine the consistency of each data that is monitored with IoT. The examined outcomes with five scenarios process that projected model on offloading analysis with block chain proves to be more secured thereby increasing the accuracy of data processing for each IoT applications to 89%. [ABSTRACT FROM AUTHOR]