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With the increasing risks of Internet of vehicles (IoV) attack, the network security threats of vehicle-mounted systems, vehicle-mounted terminals, vehicle-mounted information and service applications, the operation and service platform of intelligent connected vehicles (ICVs) are prominent.Information tampering and virus intrusion in the generalized network attack have been proved to be suitable for the attack of ICVs.The characteristics of weak password authentication and weak encryption in traditional IoV are hard to satisfy the current requirements of multi-network and multi-node security protection in the field of IoV.In addition, the lack of domestic security encryption authentication mechanism and the imperfect encryption authentication system make it more difficult to satisfy the requirements of IoV security.To solve the problem of IoV security encryption authentication, the paper studies IoV security encryption authentication technology in the age of big data.Firstly, this paper introduces the current situation and relevant concepts of IoV security in the era of big data.Then it contrasts and analyzes the current IoV security architecture, and puts forward IoV security encryption authentication system in the era of big data, and elaborates systematically the IoV security technology architecture and the encryption authentication way of IoV communication module.Then the architecture proposed in this paper is compared with the information security standards of the IoV and elaborates key technology and innovations of the IoV security encryption authentication.Finally, the paper summarizes and proposes the problems and challenges faced by the current security encryption authentication technology of IoV.

Evolutionary game theory involves multiple disciplinary sciences and has enormous scientific value and promising applicability. Collective behavior is an important topic of interdisciplinary study. Ethology has shown the ubiquity of collective behavior and has proven the rationality of evolutionary theory in explaining the emergence of collective behavior. The recent development of complex network theory offers a convenient framework for describing game interactions and competition relationships among individuals. The combination of evolutionary games and complex networks, particularly, evolutionary game theory in a complex network, has been attracting growing interest from different fields. It has undergone substantial development, especially in quantitative analysis of two-strategy competition. Under this framework, the complex network represents the population structure, and the game describes interactions between individuals. On the basis of the methodology from network science, stochastic process, and statistical physics, the framework mainly focuses on how population structures, individual behavior patterns, and interacting environments influence the emergence of collective behavior. In this paper, the mechanisms for the evolution of cooperation were given under the framework of evolutionary game, including kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. Recently, the effects of individual heterogeneity and environmental feedback on cooperation had attracted growing interest. Next, five main theoretical methods were addressed for analyzing the evolutionary game in complex networks, including the \begin{document}$ \sigma $\end{document}- dominance rule, the coalescing theory, the pairwise approximation, the coalescing random walk theory, and the adaptive dynamics. Particularly, the recently proposed coalescing random walk theory is suitable for analyzing the dynamics of any network structure and any update rule. Then, the studies on the evolution of fairness in ultimatum games were presented, and reasonable resource allocation is the key factor for social stability, economic development, and individual health. Finally, the challenges and further directions of studying ultimatum games in a complex network were summarized.