Self-adaptive early warning method and system for cross-space cascading faults in power grid cyber-physical systems

Abstract

The invention discloses a grid cyber-physical system (Grid Cyber-Physical Systems, GCPS) cross-space cascading fault self-adaptive early warning method, which is suitable for the grid cyber-physical system cross-space cascading fault (Cascading The adaptive early warning method of Failures Across Space (CFAS) includes two parts: the GCPS operation state transition model considering the impact of CFAS periodic failure hazards, and the CFAS adaptive early warning process that tolerates periodic fault hazards. The CFAS self-adaptive early warning method proposed by the present invention can accurately determine the type of CFAS implemented by an attacker and its evolution process, and can assist GCPS defenders in timely blocking the continued evolution of CFAS under the condition of avoiding the confusion of interfering network attacks.

Description

technical field [0001] The invention belongs to the field of grid cyber-physical systems (GridCyber-Physical Systems, GCPS) security protection, and relates to a cross-space cascading fault self-adaptive early warning method and system for a grid cyber-physical system that tolerates periodic fault hazards. Background technique [0002] Attackers can cause a series of spatio-temporal coordinated physical faults on multiple power grid physical nodes through coordinated network attacks, forming large-scale cross-space cascading faults (Cascading Failures Across Space, CFAS), resulting in reduced safety margins of power grid physical systems, and even Large-scale power outages have seriously affected the stable operation of GCPS. Accurate early warning during the evolution of CFAS can assist GCPS defenders to take effective protective measures to block or delay the continued development of CFAS and improve the ability of GCPS to resist malicious attacks. [0003] At present, th...

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Problems solved by technology

[0003] At present, the research on CFAS early warning methods is in its infancy. The research content is mostly the formation mechanism and detection methods of small-scale power grid physical faults caused by network attacks. It is difficult to accurately identify the CFAS implemented by attackers: First, the existing research objects are only network attacks. The small-scale physical faults caused by it do not fully consider the space-time coordination relationship between multiple physical faults in CFAS, and it is difficult to infer the type of CFAS and its evolution trend; second, the existing fault detection methods work in a "zero tolerance to harm" manner It is difficult to provide effective decision-making support for blocking the evolution of CFAS. It will alert immediately after potential faults are discovered, which is likely to generate a large number of false alarms, and even cause GCPS defenders to be misled by disruptive network attacks and take wrong handling methods, which further expands the damage of faults and causes The frequent actions of the three lines of defense of the power system and the blackout defense system consume limited defense resources and reduce the resilience of GCPS

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