Evaluation of Cross-Layer Network Vulnerability of Power Communication Network Based on Multi-Dimensional and Multi-Layer Node Importance Analysis

With the increasing complexity of environments and the diversity of task chains, individual unmanned aerial vehicles (UAVs) often struggle to satisfy the demands of task chains, including load capacity improvement, information perception, and information procession. In complex task chains involving various UAVs, such as area reconnaissance and fire rescue, any attack on critical UAVs can greatly disrupt the execution of the entire task chain by causing equipment damage or connectivity disruption. To ensure network resilience post attack, identifying vulnerable nodes in the UAV network becomes crucial. In this paper, a Vulnerability-based Topology Reconstruction Mechanism (VUTRM) is proposed to rank the importance of nodes in task chains and formulate a topology reconstruction. It consists of two parts: the first part is a Multi-metric Node Vulnerability Assessment Algorithm (MENVAL) used to rank the importance of nodes in task chains, and the second part is a Node Importance-based Topology Reconstruction Algorithm (NITRA) used to reconstruct the UAV network with the obtained node ranking. Finally, simulations carried out with simulation software demonstrate that our proposed method accurately identifies network vulnerabilities and promptly implements effective reconstruction measures to minimize network damage.

Section: Related Workmentioning

confidence: 99%

Vulnerability Assessment and Topology Reconstruction of Task Chains in UAV Networks

Yue,

Li,

Huang

et al. 2024

“…The power communication network is an important component of the smart grid, and the backbone network consists of exchange nodes and fiber optic links, carrying out the services of power grid production and operation. The transmission and exchange of service data are closely related to the safe operation of the power grid [4,5]. In the pursuit of high-quality power grid development, the variety and number of services continue to grow, and it is necessary to ensure the reliability and effectiveness of power communication network service transmission [6].…”

Section: Introductionmentioning

confidence: 99%

Research on Power Service Route Planning Scheme Based on SDN Architecture and Reinforcement Learning Algorithm

Lv,

Wei,

et al. 2024

The power communication network carries various power services to ensure the safe operation of the power network, among which, the relay protection service is the most important service. Reasonable planning of the service route can improve the effectiveness and reliability of data transmission in the power communication network, thereby ensuring the reliable operation of the power grid. This paper constructs a route planning architecture for the power communication network based on a software-defined network. On this basis, parameters such as the power service and network-carrying service status are defined. With the goal of minimizing network risk variance and considering link bandwidth utilization and overload constraints of relay protection services, a service route allocation problem has been raised. To solve this problem, a power service route planning scheme based on a reinforcement learning algorithm is proposed. This algorithm uses the state–action–reward–state–action (SARSA) algorithm to complete service route planning. The simulation results show that using the route planning scheme proposed in this paper can avoid the overload of relay protection services, reduce network risk variance, and effectively balance network risk.

“…Based on the technique for order preference by similarity to an ideal solution (TOPSIS) method and the criteria importance through intercriteria correlation (CRITIC) method, a critical node identification method of power grid is established in [11]. In [12], the network topology is divided into three dimensions for analysis. Then, a multidimensional and multilayer node evaluation model based on the entropy weight method (EWM) is proposed in [12], considering the connection relationship between power grid and the communication network.…”

Section: Introductionmentioning

confidence: 99%

“…In [12], the network topology is divided into three dimensions for analysis. Then, a multidimensional and multilayer node evaluation model based on the entropy weight method (EWM) is proposed in [12], considering the connection relationship between power grid and the communication network. To prevent cascading failures in power systems, Ref.…”

Section: Introductionmentioning

confidence: 99%

Critical Node Identification Method of Power Grid Based on the Improved Entropy Weight Method

Zhang

Wang

et al. 2023

It is very important to accurately identify the critical nodes of the power grid for its safe and stable operation. In this paper, a method for identifying the critical nodes of the power grid based on the improved entropy weight method (IEWM) is proposed, and the IEWM corrects issues with the information overlap between evaluation indices and inconsistency between the entropy weight (EW) and entropy value (EV). First, considering the power grid topology and operating conditions, structural factor evaluation indices and state factor evaluation indices are established. On this basis, the IEWM is used to assign weights to nodes with different voltage levels, which strengthens the consideration of node voltage levels in the identification method of critical nodes and makes the results more accurate and effective. Simulation experiments of IEEE 30-bus and IEEE 118-bus systems verify the accuracy of the critical node identification method proposed in this paper.