Blockchain-based agricultural IoT systems face key challenges, such as high delay and low-transaction throughput. Existing complicated consensus mechanisms can cause IoT devices work inefficiently due to the limited computing, storage and energy resources. Additionally, many message exchanges can lead to high latency in the consensus process, which hinders the real-time applications of the agricultural IoT. Therefore, we propose Proof-of-Multifactor-Capacity (PoMC), an efficient and secure consensus mechanism for the agricultural IoT. It uses the communication capacity and credibility of a node as the evidence for making consensus. Moreover, a senator node lottery algorithm based on a credit mechanism and a new distributed incentive mechanism are designed to enhance security and motivate nodes to actively maintain the system. This article analyses the performance of PoMC theoretically, including security, latency, and system throughput, and presents a comparison of its asymptotic complexity with some existing consensus mechanisms. The simulation results demonstrate that the average transaction validation latency and average consensus latency of PoMC have decreased by 10% and 23%. In addition, PoMC outperforms SENATE, PoQF and practical Byzantine fault tolerance (PBFT) by 56%, 60% and 64% in terms of the system throughput, respectively.

The requirements for large amounts of data have promoted the rapid emergence of an industry for trading data. However, the current one-to-one trading constraints in the existing data trading schemes lead to low security and low efficiency. To tackle the challenges, a novel one-to-many distributed data trading scheme is proposed based on blockchain, which enables a data seller to sell one piece of data to multiple data buyers simultaneously, saving storage resources and computing resources significantly. Firstly, some new smart contracts are devised for two decentralized applications. Then, attribute-based searchable encryption technology is proposed to establish a data circulation scheme that realizes end-to-end encryption of data and ensures data security and highly efficient access. Finally, an inspection mechanism based on zero-knowledge proof and a pricing strategy based on the Stackelberg game are designed to guarantee fairness in trading and maximize revenue. The experiment results show that, in comparison to one-to-one trading, the high efficiency of this data trading scheme gradually emerges as the number of buyers (n) is greater than 2, and the run time is less than 1/10 of the former when n =35. Furthermore, the pricing strategy can enable buyers and sellers to obtain more revenue when$\text {n} \gt 4$.

Data access control in a cloud storage system is regarded as a promising technique for enhanced efficiency and security utilizing a ciphertext-policy attribute-based encryption (CP-ABE) approach. However, due to a large number of data users as well as limited resources and heterogeneity of data devices in Internet of Things (IoT), existing access control schemes for the cloud storage are not effectively applicable to IoT applications. In this article, we construct a new CP-ABE-based storage model for data storing and secure access in a cloud for IoT applications. Our new framework introduces an attribute authority management (AAM) module in the cloud storage system functioned as an agent that provides a user-friendly access control and highly reduces the storage overhead of public keys. Then, we propose a novel secure and efficient multiauthority access control scheme of the cloud storage system for IoT, namely, SEM-ACSIT, which obtains both backward security and forward security when an attribute of a user is revoked. By exploiting encryption outsourcing, simplified key structuring and the AAM module, the computational overhead of a user is immensely decreased. Moreover, a user access control list (UACL) in the cloud server is constructed newly to support authorization access for a specific user. The analysis and simulation results demonstrate that our SEM-ACSIT scheme achieves powerful security with less computational overhead and lower storage costs than the existing schemes.

Large-scale and heterogeneity of the Internet of Things (IoT) sensing networks introduce a big challenge to device connectivity. There exist some isolated nodes in randomly deployed IoT sensing networks running on a tree-typed topology due to limitations of some network parameters, which reduces network connectivity. In this paper, a connectivity enhancement scheme for the sensing networks of the IoT is proposed based on link transformation. Under constraints of network depth and the number of child nodes, we boost capability of an in-network node to connect more isolated nodes by reducing its or ancestors' depth. Furthermore, three-level node shifting is utilized to take full advantage of network locality, thus highly improving ability of a potential parent node to accept connection request of an isolated node. Finally, when failing to reduce depth of a node and disabling to shift out a child node of a parent node, the scheme exploits node swapping to improve present link status, thus enabling further some isolated nodes to join into the sensing networks. Our simulation results show that the proposed scheme can raise proportion of joined nodes and effectively enhance connectivity of the sensing networks in the IoT.