Information Security Risk Propagation Model Based on the SEIR Infectious Disease Model for Smart Grid

Abstract

With the high integration of smart grid information and physical systems, the security of information systems must affect the safe and stable operation of physical systems. Risk assessment is an effectual means to objectively evaluate the information security threats of the smart grid. However, the existing risk assessment methods are aim at solving the threat of security risks in communication networks and information systems in the smart grid, but there is no in-depth study on how the spread of information security risks between information systems and physical systems in the smart grid. Therefore, based on the traditional infectious disease transmission theory, the information security risk propagation model based on the Susceptible–Exposed–Infected–Recovered (SEIR) infectious disease model for smart grid (ISRP-SEIRIDM) is proposed in this paper. In ISRP-SEIRIDM, we analyze the information interaction between information collection devices and define the connection of nature and the security risks between the information collection devices in the smart grid. At the same time, we also study the impact of the number of information acquisition devices and information interaction capabilities of these devices on the speed of security risk transmission between information systems and physics systems in the smart grid and the maximum risk range. Experimental results show that the risk propagation range can be significantly reduced by optimizing the data interaction capability and information transmission path between information collection devices in the smart grid; when a probability from a susceptible state to an exposed state reduces by 0.15, the maximum spread and average spread of security risk will be reduced by 7% and 1.96%, respectively.

Cyber Risk Propagation and Optimal Selection of Cybersecurity Controls for Complex Cyberphysical Systems

“…Percolation theory was also used in Reference [ 24 ] to analyze the propagation of node failures in a network of CPSs comprising cyber and physical nodes organized in two distinct layers, such as in the case of the power grid. The Susceptible–Exposed–Infected–Recovered (SEIR) infectious disease model was used in Reference [ 25 ] to study malware infection propagation in the smart grid. A quantitative risk assessment model that provides asset-wise and overall risks for a given CPS and also considers risk propagation among dependent nodes was proposed in Reference [ 26 ].…”

Machine Learning-Based Node Characterization for Smart Grid Demand Response Flexibility Assessment

“…Information security is discussed in [12], where risk propagation model based on the Susceptible-Exposed-Infected-Recovered (SEIR) infectious disease model is proposed for a smart grid. The high volatility and uncertainty of load profiles and the tremendous communication pressure are discussed in a two-stage household electricity demand estimation study by [13].…”

Multi-Player Evolutionary Game of Network Attack and Defense Based on System Dynamics

“…Based on dynamic game models, Laszka et al [22] proposed a multi-attribute utility-based game model by assuming that the attacker knows all of the defender's strategies. Zhu et al [23] proposed a new state evolution model for network security based on the infectious disease model. Wang et al [24] portrayed the possible dynamic characteristics of the attack and defense of the grid system in a controlled environment and proposed a boundary between attack and defense.…”