A Framework of Hierarchical Attacks to Network Controllability

Abstract

Network controllability robustness reflects how well a networked dynamical system can maintain its controllability against destructive attacks. This paper investigates the network controllability robustness from the perspective of a malicious attack. A framework of hierarchical attack is proposed, by means of edge- or node-removal attacks. Edges (or nodes) in a target network are classified hierarchically into categories, with different priorities to attack. The category of critical edges (or nodes) has the highest priority to be selected for attack. Extensive experiments on nine synthetic networks and nine real-world networks show the effectiveness of the proposed hierarchical attack strategies for destructing the network controllability. From the protection point of view, this study suggests that the critical edges and nodes should be hidden from the attackers. This finding helps better understand the network controllability and better design robust networks.

arXiv comment10 pages,10 figures

References in corpus (18)

• Attack vulnerability of complex networks
• Renormalization group analysis of the small-world network model
• Universal Behavior of Load Distribution in Scale-free Networks
• Mitigation of Malicious Attacks on Networks
• Control Principles of Complex Networks
• Exact Controllability of Complex Networks
• Robustness of interdependent networks under targeted attack
• Control centrality and hierarchical structure in complex networks
• The extreme vulnerability of interdependent spatially embedded networks
• Effect of correlations on network controllability
• Network Controllability Is Determined by the Density of Low In-Degree and Out-Degree Nodes
• Percolation of partially interdependent networks under targeted attack
• Networkcontrology
• Effects of the network structural properties on its controllability
• Predicting Network Controllability Robustness: A Convolutional Neural Network Approach
• Complex networks vulnerability to module-based attacks
• Toward Stronger Robustness of Network Controllability: A Snapback Network Model
• Towards Optimal Robustness of Network Controllability: An Empirical Necessary Condition

Cited by in corpus (2)

• Structural Robustness of Complex Networks: A Survey of A Posteriori Measures
• CNN-based Prediction of Network Robustness With Missing Edges