In modern smart grid networks, the traditional power grid is empowered by technological advances in sensing, measurement, and control devices with two-way communications between the suppliers and consumers. The smart grid integration helps the power grid networks to be smarter, but it also increases the risk of attacks because of the existing obsolete cyber-infrastructure. In this article, we focus on bad data injection attacks for smart grid. The basic problem formulation is presented, and the special type of stealth attack is discussed. Then we investigate the strategies of defenders and attackers, respectively. Specifically, from the defender's perspective, an adaptive cumulative sum test is able to determine the possible existence of adversaries at the control center as quickly as possible. From the attacker's point of view, independent component analysis is employed for the attackers to make inferences through phasor observations without prior knowledge of the power grid topology. The inferred structural information can then be used to launch stealth attacks.

Smart pricing methods using auction mechanism allow more information exchange between users and providers, and they can meet users' energy demand at a low cost of grid operation, which contributes to the economic and environmental benefit in smart grid. However, when asked to report their energy demand, users may have an incentive to cheat in order to consume more while paying less, causing extra costs for grid operation. So it is important to ensure truthfulness among users for demand side management. In this paper, we propose an efficient pricing method that can prevent users' cheating. In the proposed model, the smart meter can record user's consumption information and communicate with the energy provider's terminal. Users' preferences and consumption patterns are modeled in form of a utility function. Based on this, we propose an enhanced AGV (Arrow-d'Aspremont-Gerard-Varet) mechanism to ensure truthfulness. In this incentive method, user's payment is related to its consumption credit. One will be punished to pay extra if there is a cheat record in its consumption history. We prove that the enhanced AGV mechanism can achieve the basic qualifications: incentive compatibility, individual rationality and budget balance. Simulation results confirm that the enhanced AGV mechanism can ensure truth-telling, and benefit both users and energy providers.

As the current power grid system is upgrading to the smart grid, it becomes more vulnerable to security attacks on its communication subsystem such as the denial-of-service attack. Jamming, as a kind of denial-of service attack, can be applied to interfere the real-time communication in smart grid. In this paper, we analyze the scenario in which the attacker can jam a reduced number of signal channels carrying measurement information in order to manipulate the locational marginal price and create the opportunity for gaining profit, and the defender is able to guarantee a limited number of channels in information delivery. Based on the electricity marketing model, we propose a multiact dynamic game between the attacker and defender, in which the optimal strategies are taken by the two sides to maximize their own profits. We study the gaming process and discuss the prosperities of the outcome. Simulation results present the affect of jamming attack on the electricity prices and the gained profits of the two sides. Moreover, they confirm the optimality of the proposed scheme in pursuing profit.

Applications of cyber technologies improve the quality of monitoring and decision making in smart grid. These cyber technologies are vulnerable to malicious attacks, and compromising them can have serious technical and economical problems. This paper specifies the effect of compromising each measurement on the price of electricity, so that the attacker is able to change the prices in the desired direction (increasing or decreasing). Attacking and defending all measurements are impossible for the attacker and defender, respectively. This situation is modeled as a zero-sum game between the attacker and defender. The game defines the proportion of times that the attacker and defender like to attack and defend different measurements, respectively. From the simulation results based on the PJM 5-Bus test system, we can show the effectiveness and properties of the studied game.

Device-to-device (D2D) communication is viewed as one promising technology for boosting the capacity of wireless networks and the efficiency of resource management. D2D communication heavily depends on the participation of users in sharing contents. Thus, it is imperative to introduce new incentive mechanisms to motivate such user involvement. In this paper, a contract-theoretic approach is proposed to solve the problem of providing incentives for D2D communication in cellular networks. First, using the framework of contract theory, the users' preferences toward D2D communication are classified into a finite number of types, and the service trading between the base station and users is properly modeled. Next, necessary and sufficient conditions are derived to provide incentives for users' engagement in D2D communication. Finally, our analysis is extended to the case in which there is a continuum of users. Simulation results show that the contract can effectively incentivize users' participation, and increase capacity of the cellular network than the other mechanisms.