To solve issues of frequent network topology changes to slow consensus speed, and low security in consensus algorithms within heterogeneous dynamic IoT systems, we propose a fast consensus algorithm of large-scale heterogeneous dynamic IoT nodes for DAG-based blockchain, LSHD_DAG. Firstly, an adaptive regional division method for heterogeneous dynamic nodes is proposed, which monitors nodes’ state and counts within each region, adjusting the boundaries of adjacent regions. Secondly, an event-triggered master-slave DAG chain design is proposed. When transaction information pertains to a single region, the transaction is processed as a local transaction to construct a regional DAG slave chain. If transaction information involves multiple regions, it is organized into a multi-regional transaction set and incorporated into the global DAG master chain. Next, a node grade identification mechanism that balances state and reputation factors is proposed. This mechanism adopts the LOF algorithm to classify or dynamically update node grades by considering node state and reputation evaluation results, assigning them identity permissions. Finally, a weighted voting consensus based on the master-slave DAG chain is introduced. Nearby honest nodes with stable movement are selected as consensus nodes, which perform multi-regional weighted voting consensus on transactions and transaction sets. This process concludes with Two-Way Pegging with multi-signature on the master-slave DAG, ensuring secure and rapid consensus for data in heterogeneous and dynamic IoT environments. The experimental results show that no matter how the number of nodes changes, LSHD_DAG can improve transaction throughput, and reduce latency and communication overhead, outperforming the CDBFT, DAG-D, and Avalanche.

In order to solve the problems in the blockchain consensus algorithm, such as slow consensus speed, high resource consumption, and low consensus security due to excessive large-scale node data volume and Byzantine attacks in the Internet of Things (IoT) system, we propose a large-scale node lightweight consensus algorithm of blockchain for IoT (LNLCA). First, a transaction set construction mechanism is proposed to improve consensus efficiency and security. The mechanism packages multiple data monitored by IoT nodes into data transactions, and builds the transaction set. Then, it constructs nonconflict subsets and conflict subsets. Second, an adjacent parent node sampling and response mechanism is proposed to reduce the consumption of communication resources. The new transaction set selects nearby parent nodes based on the time distance summation method and collaborates to batch verify each transaction in the transaction set. Finally, an efficient consistent consensus based on transaction set directed acyclic graph (DAG) is proposed to quickly vote for each transaction in the transaction set, thereby constructing the transaction set DAG for batch uploading to the chain, and achieving a secure and lightweight consensus on IoT data. The experimental results show that no matter how the number of Byzantine nodes changes, LNLCA can improve transaction throughput, and reduce transaction delay and communication overhead, which outperforms the credit-delegated Byzantine fault tolerance, Avalanche, and Hashgraph.

With the Industrial Internet of Things (IIoT) continuing to expand, lots of data collection, exchange, and authentication generated from an increasing number of access devices is required with heterogeneity, multidimension, and multiobjective networks as its characteristics. However, traditional IIoT systems are vulnerable to security challenges, such as data leakage, theft, and tampering. As one of the most promising solutions, blockchain has played an essential role in ensuring security and transparency in the IIoT. But there are still some challenges that prevent the secure and effective implementation of blockchain-based IIoT systems in consensus security, consensus efficiency, and consensus application. To address these problems, we propose an effective security blockchain consensus algorithm for heterogeneous IIoT nodes aiming to defend against the consensus attack and improve consensus efficiency. First, we design a blockchain-based IIoT system architecture. Then, we present an identity authentication and transformation protocol to defend against consensus attacks. Furthermore, we introduce a method for constructing communication directed acyclic graphs (DAGs) and transaction set DAGs to enhance transaction throughput. Based on these two DAGs, we propose an efficient and security consensus algorithm (DAG-D). DAG-D employs transaction sets instead of single transactions or blocks, leveraging communication DAG propagation to swiftly confirm transaction set DAGs based on parent transactions for associated confirmation. Experimental results show that our proposed DAG-D outperforms DAG-M, DAG-Avalanche, and DAG-CoDAG, regarding transaction throughput, transaction latency, and communication overhead.

Owing to the incremental and diverse applications of cryptocurrencies and the continuous development of distributed system technology, blockchain has been broadly used in fintech, smart homes, public health, and intelligent transportation due to its properties of decentralization, collective maintenance, and immutability. Although the dynamism of blockchain abounds in various fields, concerns in terms of network communication interference and privacy leakage are gradually increasing. Because of the lack of reliable attack analysis systems, fully understanding some attacks on the blockchain, such as mining, network communication, smart contract, and privacy theft attacks, has remained challenging. Therefore, in this study, we examine the security and privacy of the blockchain and analyze possible solutions. We systematical classify the blockchain attack techniques into three categories, then discuss the corresponding attack and defense methods based on these categories. We focus on (1) the attack and defense methods of mining pool attacks for blockchain security issues, such as block withholding, 51%, pool hopping, selfish mining, and fork after withholding attacks, in the attack type of consensus excitation; (2) the attack and defense methods of network communication and smart contracts for blockchain security issues, such as distributed denial-of-service, Sybil, eclipse, and reentrancy attacks, in the attack type of middle protocol; and (3) the attack and defense methods of privacy thefts for blockchain privacy issues, such as identity privacy and transaction information attacks, in the attack type of application service. Finally, we discuss future research directions for blockchain security.

Considering the competition between rescue points, we use artificial intelligence (AI) driven Internet of Thing (IoT) and regional material storage data to propose a multiobjective scheduling algorithm of flood control materials based on Pareto artificial bee colony (MSA_PABC). To address the scheduling of flood control materials, the multiple types of flood control materials, the multiple disaster sites, and entertain both emergency and fairness of rescue need to be considered comprehensively. The MSA_PABC has the constraints such as storage quantity constraint of warehouse materials, material demand constraint, and maximum transportation distance of flood control materials. We establish the scheduling optimization model of flood control materials for each disaster rescue point and the total scheduling optimization model for all flood control materials. Then, MSA_PABC uses the modified Pareto artificial bee colony algorithm to solve the multiobjective models. Three types of initialization strategies are proposed to calculate the fitness of each rescue point and the overall evaluation value of the food source. We propose the employ bee operations such as niche technology and local search of the variable neighborhood, the onlooker bee operations such as Pareto nondominated sorting and crossover operation, the scout bee operations such as maximum evolutionary threshold, and end elimination mechanism. Finally, our proposed solution obtains the nondominated solution set and its optimal solution. The experimental results show that no matter how the number of rescue points changes, MSA_PABC can find the nondominated solution set and optimal solution quickly. It improves the convergence rate of MSA_PABC and material satisfaction rate. Our solution also reduces the average maximum transportation distance, the standard deviation of maximum transportation distance, and the standard deviation of material satisfaction rate. The evaluation also demonstrates MSA_PABC outperforms the state‐of‐arts such as ABC (artificial bee colony), NSGA2 (nondominated sorting genetic algorithm 2), and MOPSO (multiobjective particle swarm optimization).

To solve the problem of sensing coverage of sparse wireless sensor networks, the movement of sensor nodes is considered and a sensing coverage algorithm of sparse mobile sensor node with trade-off between packet loss rate and transmission delay (SCA_SM) is proposed. Firstly, SCA_SM divides the monitoring area into several grids of same size and establishes a path planning model of multisensor nodes’ movement. Secondly, the social foraging behavior of Escherichia coli in bacterial foraging is used. A fitness function formula of sensor nodes’ moving paths is proposed. The optimal moving paths of all mobile sensor nodes which can cover the entire monitoring area are obtained through the operations of chemotaxis, replication, and migration. The simulation results show that SCA_SM can fully cover the monitoring area and reduce the packet loss rate and data transmission delay in the process of data transmission. Under certain conditions, SCA_SM is better than RAND_D, HILBERT, and TCM.