# MADDPG-Based Security Situational Awareness for Smart Grid with Intelligent Edge
## 1 Introduction  
With the rapid development of wireless communication and the internet of things (IoT) technologies, the explosive growth of intelligent terminals access to smart grids [1, 2]. By taking advantages of massive data generated from a huge number of intelligent terminals, data-driven control can leverage these data to identify different situations for making decisions, which is vital for production and operation in smart grids [3, 4]. However, while these new technologies facilitate smart grid services, they may also bring new security challenge issues [5, 6, 7]. Attacks in the power IoT environment have increased substantially in both number and variety, causing significant damage to the grid. For instance, a cyber threat on the Ukrainian power grid left 225,000 people powerless for several days in December 2015 [8]. A physical attack on a California substation in April 2014 severely impacted the operation of the grid [9], and the economic and environmental losses caused by such attacks are immeasurable. These examples show that the threat problem of the grid exists. If not handled properly, it will have a significant impact on people's productive life. Therefore, a smart grid with high-security requirements should be able to monitor fault information during its operation. Before an attack happens, it is necessary to automatically cut off the threat in time and repair the fault automatically to ensure the grid system's stable operation. Today, security situational awareness (SSA) and prediction are essential functions and necessary measures to satisfy the power system's process in smart grids' information management system [10,11]. The application and development of network SSA technology in smart grids enables the acquisition, understanding, and prediction of various security factors. Moreover, it can accurately grasp the grid's security situation and achieve proactive prevention of grid security threats. Most SSA research works for smart grids currently have relied on data acquiring devices that gather information from various power terminals or sensors [12,13]. Then this collected information would be uploaded to the power master station for further aggregation and analysis to obtain security measures applicable to multiple power systems [14, 15, 16]. However, the deployment of actual SSA technology faces many critical issues in smart grids. 1. With massive heterogeneous power terminals and distinct communication protocols, causing interconversion and interoperability trouble in network communication. Moreover, there are considerable challenges in heterogeneous network deployment and configuration, network management, and maintenance. Therefore, the effective deployment of the massive heterogeneous terminals is necessary. 2. The smart grid control system must always be up to running and should be addressed promptly in the face of real-time threats. SSA technology in smart grids master station based on cloud computing does not satisfy the requirement of dealing with real-time threats. Therefore, low latency SSA technology is necessary. 3. The network of smart grids is particular and requires exceptionally high-security performance. Once attacked, it will face huge losses. Therefore, high-efficiency and high-precision SSA technology are necessary. In such cases, the integration of edge computing and artificial intelligence (AI) into SSA technologies for smart grids can solve the above problems. Edge computing [17] enables an open platform combining connectivity, computation, storage, and application at the edge side of the system's network to provide edge intelligence services for data from power sensing nodes nearby. Deploying corresponding intelligent edge agents for different power terminal clusters solves massive heterogeneous networks and transmission and processing delays. For the security of the smart grid, the existing power system situational awareness mainly adopts the defense means of automatically detecting and then disconnecting or replacing the faulty electronic components.