Vehicular ad‐hoc network (VANET) plays a vital role in the intelligent transportation system. It is crucial to ensure secure communication among entities in the VANET for realizing an efficient transportation system. In this scenario, the current communication scheme is vulnerable to the leakage of private information from entities. The research primarily centers on single‐domain vehicular networks, with only a limited number of researchers exploring cross‐domain authentication among vehicle entities. Cross‐domain communication schemes have received little attention from scholars. Furthermore, there are issues, including the susceptibility of in‐vehicle conversations to eavesdropping, the vulnerability of long‐distance transmissions to interruptions, and the exposure of wireless networks to traffic attacks. To address these issues, a multidomain secure communication and intelligent traffic detection model in VANET is proposed. This model offers several notable advantages as follows: (1) It employs a key self‐verification algorithm for local computation and authentication of entity keys. This approach mitigates the risks of identity impersonation attacks and key leakage results from third‐party key escrow. (2) A multidomain communication scheme is devised to categorize vehicle‐to‐vehicle (V2V) scenarios into intradomain and interdomain, which correspond to situations where the communicating parties are within the same domain and across different domains, respectively. (3) We propose the implementation of new session message encryption algorithms for V2V communication. This involves generating dynamic random keys to ensure secure data sharing and facilitates long‐distance cross‐domain communication among vehicles. (4) An intelligent two‐layer traffic detection paradigm is proposed to improve the efficiency of detecting attack traffic in vehicular networks. This paper provides security proofs and performance analysis of the proposed scheme. The experimental results demonstrate that within the communication module, the comparative scheme exhibits high computational demands and significant delays, whereas our approach provides superior security and better computational performance. Compared to the traditional detection model, our two‐layer detection paradigm reduces model training time by 69–4477 ms and testing time by 9–1469 ms.

Secure data-sharing technology is a bridge for various collaborative operations among intelligent terminals in the edge-cloud collaborative application scenario. For the shared data involves different levels of confidentiality, intelligent terminals for collaborative operations may be distributed in multiple management domains, and the private information of intelligent terminals is easy to be leaked in edge-cloud collaboration scenarios, the security of data sharing is severely threatened. To solve these problems, this paper proposed a fine-grained and traceable multidomain secure data-sharing model for intelligent terminals. In this model, a key self-certification algorithm is proposed, which avoids potential security threats of key leakage during the key distribution process. The model combines attribute encryption and threshold function to achieve more fine-grained and more flexible secure data sharing; it uses blockchain technology to achieve integrity verification of stored data and traceability of shared data, and it combines on-chain and off-chain databases to achieve rapid retrieval and positioning of shared data distributed among multiple domains, which improves the efficiency of data sharing among domains. The security of the model proposed by us is proved, and compared with the cited literature, it is shown that the proposed model has certain advantages in terms of computational complexity and time consumption.

The application of intelligent computing in Internet of Things (IoTs) makes IoTs systems such as telemedicine, in-vehicle IoT, and smart home more intelligent and efficient. Secure communication and secure resource sharing among intelligent terminals are essential. A secure communication channel for intelligent terminals can be established through group key agreement (GKA), thereby ensuring the security communication and resource sharing for intelligent terminals. Taking into account the confidentiality level of the shared resources of each terminal, and the different permissions of the resource sharing of each terminal, a GKA protocol for intelligent IoTs is proposed. Compared with previous work, this protocol mainly has the following advantages: (1) The hidden attribute identity authentication technology can achieve the security of identity authentication and protect personal privacy from being leaked; (2) Only intelligent terminals satisfying the threshold required of the GKA can participate in the GKA, which increases the security of group communication; (3) Low-level group terminals can obtain new permissions to participate in high-level group communication if they meet certain conditions. High-level group terminals can participate in low-level group communication through permission authentication, which increases the flexibility and security of group communication; (4) The intelligent terminals in the group can use their own attribute permission parameters to calculate the group key. They can verify the correctness of the calculated group key through a functional relationship, and does not need to exchange information with other members in the same group. Under the hardness assumption of inverse computational Diffie-Hellman problem and discrete logarithm problem, it is proven that the protocol has high security, and compared with the cited literatures, it has good advantages in terms of computational complexity, time cost and communication energy cost.

Security communication and information sharing among mobile devices are important application technologies of the intelligent information system (IIS). Because IIS is vulnerable to attacks, so the security of information sharing among mobile devices is seriously threatened. Thence, it is necessary to establish a secure channel for communication among mobile devices of IIS over an opening network. Group key agreement (GKA) can establish a secure channel among mobile devices of IIS by encryption technology. Due to the resource-constraints of mobile devices, such as weak computing power, small storage capacity, and limited communication range. To address these issues, an asymmetric GKA protocol among terminals of IIS for mobile edge computing (GKA–IIS–MEC) network is proposed in this paper. Adopted asymmetric GKA to achieve the group secure communication mechanisms that message sender unfettered in this protocol; the protocol also uses edge computing environment to migrate the computation and communication loads of mobile devices of IIS to edge nodes, thereby ensuring that mobile devices have lightweight computation and communication loads; and the members participating in the GKA can verify whether the group session keys they calculated are correctness. Under the hardness assumption of bilinear inverse Diffie–Hellman problem, the proposed protocol is proven that it can resist negative attacks. After evaluating the performance of the protocol, GKA–IIS–MEC has higher efficiency than the referred works in terms of time cost, communication consumption, and computation consumption.

With the widespread application of Industrial Internet of Things (IIoT) technology in the industry, the security threats are also increasing. To ensure the safe sharing of resources in IIoT, this paper proposes a data security sharing model based on privacy protection (DSS-PP) for blockchain-enabled IIoT. Compared with previous works, DSS-PP has obvious advantages in several important aspects: (1) In the process of identity authentication, it protects users' personal information by using authentication technology with hidden attributes; (2) the encrypted shared resources are stored in off-chain database of the blockchain, while only the ciphertext index information is stored in the block. It reduces the storage load of the blockchain; (3) it uses blockchain logging technology to trace and account for illegal access. Under the hardness assumption of Inverse Computational Diffe–Hellman (ICDH) problem, this model is proven to be correct and safe. Through the analysis of performance, DSS-PP has better performance than the referred works.