Traffic prediction is vital to traffic planning, control, and optimization, which is necessary for intelligent traffic management. Existing methods mostly capture spatiotemporal correlations on a fine-grained traffic graph, which cannot make full use of cluster information in coarse-grained traffic graph. However, the flow variation of clusters in the coarse-grained traffic graph is more stable compared with nodes in the fine-grained traffic graph. And the flow variation of a fine-grained node is generally consistent with the trend of the cluster to which the node belongs. Thus information in the coarse-grained traffic graph can guide feature learning in the fine-grained traffic graph. To this end, we propose a Spatiotemporal Multiscale Graph Convolutional Network (SMGCN) that explores spatiotemporal correlations on a multiscale graph. Specifically, given a fine-grained traffic graph, we first generate a coarse-grained traffic graph by graph clustering, and extract spatiotemporal correlations on both fine-grained and coarse-grained traffic graphs. Then we propose a cross-scale fusion (CF) to implement information diffusion between the fine-grained and coarse-grained traffic graphs. Moreover, we employ an adaptive dynamic graph convolution network to mine both static and dynamic spatial features. We evaluate SMGCN on real-world datasets and obtain a $1.18\% -3.32\%$ improvement over state-of-the-arts.

The vehicular ad hoc network (VANET) is a basic component of intelligent transportation systems. Due to the growing security and privacy-preserving requirements of the VANET, a lot of conditional privacy-preserving authentication (CPPA) protocols have been proposed in recent years. Unfortunately, the traditional CPPA protocols, which are based on a trusted authority (TA) and rely solely on classical mathematical problems, cannot resist quantum attacks. Moreover, these protocols do not take into account the increasingly complex traffic flow in the VANET and cannot utilize fog nodes (FNs) to assist in the TA’s authentication work. In this paper, we design a lattice-based and fog-assisted conditional privacy-preserving authentication (LFCPPA) protocol to solve the above challenges. Compared to existing solutions, we have made the following improvements. First, our protocol is resistant to quantum attacks. Second, the solution supports batch processing of signature verification and mutual authentication of identity between the TA / FNs and vehicles. Third, in our design, FNs reduce the computing pressure of the TA to improve the efficiency of the system. In addition, we demonstrate the security of the protocol under the random oracle model with provable security. Finally, the efficiency and security of this scheme are better than similar solutions. Specifically, compared with the latest scheme, in terms of computational cost, our scheme is reduced by 74.47%, 85.58%, 19.69%, and 85.90% in the four stages of the protocol. Meanwhile, in terms of communication cost, our protocol reduces it by 89.98%.

With the rapid developments of Internet of Things (IoT) technologies, the security of sensitive data has attracted more and more attention for many resource-asymmetric smart environments, such as smart home, smart agriculture and so on. The resource-asymmetry environment refers to the uneven distribution of resources on different devices side, which is specifically manifested as gateway side is resource-rich, user side and device side are resource-restricted. Hence, a secure and practical authentication key establishment scheme for such smart environments is urgently needed. Recently many researchers have designed authentication and key establishment schemes for security purpose, however most of them cannot consider the excess of gateway resources and guarantee the anonymity of user, and further, they are not suitable for resource-asymmetric smart environments because they are not lightweight enough in user side and smart device side. Due to the fact that Rabin cryptosystem has the large difference in time-consuming between encryption and decryption, it is extremely suitable for constructing authentication and key establishment scheme for resource-asymmetric smart environments. So, a new practical authentication and key establishment scheme based on the Rabin cryptosystem for resource-asymmetric smart environments is proposed, which can make better use of the advantages of abundant gateway resources and realize the lightweight operations on device side and user side, and at the same time can provide user anonymity. With Proverif and BAN logic, we can prove that our solution not only provides anonymity, but also satisfies all defined security features. Simultaneously, compared with latest similar protocols in computation cost and communication overhead, the results show that our scheme is more effective. Hence, our design has more attraction for authentication and key establishment scheme in resource-asymmetric smart environments.

Reconfigurable intelligent surface (RIS) is playing a growing and ever-more significant role in constructing the six-generation (6G) wireless networks due to its properties of low cost and easy integration. Current studies about RIS-assisted communication generally assume the RISs are deployed at fixed position or devices, however, with the rapid development of unmanned aerial vehicle (UAV) technology, this readily flying wireless access platform is increasingly used to realize reliable communication. If the RISs are mounted on the random 3-D (three-dimension) mobile UAVs, how to investigate the uplink transmission of the RIS-assisted UAV communication systems would be a great challenge. To resolve this open issue, we establish a novel theoretical model to analyze the uplink performance of the RIS-assisted UAV communication systems with the random 3-D mobile pattern. In the modeling process, we first provide a random 3-D mobile model for UAVs, where the random waypoint and uniform mobility (UM) models are simultaneously used. Next, we build an end-to-end (E2E) transmission model for the RIS-assisted UAV communication system, where the impacts of channel fading type, RIS configuration, UAV’s mobility, and association policies are comprehensively considered. Combining the above two models, we derive the analytical expressions of uplink transmission metrics, and make a bound performance analysis on this base. Finally, we evaluate the uplink performance of the RIS-assisted UAV communication system with the random 3-D mobile pattern, and verify the proposed theoretical model.