# Towards Security Joint Trust and Game Theory for Maximizing Utility: Challenges and Countermeasures
## 1 Introduction  
Our demand for network performance is growing. In common networks, such as distributed networks, social networks, and centralized networks, they usually have several common goals: Maximum efficiency, profit maximization, and network security improvement. There are often some risks in the normal information transmission or interaction process. For instance, malicious attacks or deceit will reduce the security of the network and even destroy the availability of the network. In this scenario, it is of utmost importance to improve the reliability of the communication link and maximize the utility of the network. In the current big data environment, the application of sensor-cloud has higher requirements for maximizing utility [1]. In recent years, some researchers have tried to improvenetwork reliability by establishing trust models, schemes, or mechanisms, and have achieved some research results [2]. Trust concept has been widely applied in the field of network technology. Different researchers have different definitions and understandings of trust based on the different purposes and perspectives. Trust is a very broad concept, which is connected with the concepts of reliance, security, and accountability. Therefore, trust is introduced into the networks, which provides new ideas to solve the problems of network security and reliability. The application of trust in networks usually appears in the form of trust models and mechanisms. By calculating the trust value, the reliability of the network is evaluated. After determining the reliability of the network, how to choose a more efficient transmission path or information sharing party is also crucial. As a result, the application of decision mechanism has been expanded. As a decision-making theory, game theory has been introduced in networks. The game takes place under the constraints of certain game rules, based on direct interaction of environmental conditions. Each player chooses their own strategies/actions based on the information they have in order to maximize their own profit. Game theory, as a mathematical modeling method to help rational decision makers choose conflict or cooperation in order to find an optimal behavior strategy, is widely used in various fields [3], such as biology, computer science, military strategy, sociology, etc. There are some basic elements in the game, including player, strategy, payoff, outcome, and equilibrium. The basic assumption of game theory is that the decision-making subject is rational. Rationality refers to the strategy that players choose to maximize their returns, in order to maximize their payoff functions. The classification of game has different classification according to different benchmarks. According to whether a binding agreement is reached between the players, the game can be divided into cooperative game and non-cooperative game. It can be divided into static game and dynamic game according to whether the actions of the players are in order. In a static game, the latter does not know what strategy the first player has adopted. In a dynamic game, the latter can observe the choices made by the first player. According to the players' full understanding of the game strategy and other players, the game is divided into complete information game and incomplete information game. In a complete information game, each player has precise information about other players, such as the strategy space and payoff function. In an incomplete information game, at least one player does not have accurate enough information about the other players. Different types of games can be used to represent different game models. In order to have better utility, researchers have introduced the concepts of trust and game in different application scenario. By investigating the literature over the past 10 years, we have learned some of the current research status of game theory and trust. Through analysis, the application scenarios are roughly classified.