The robustness of multiplex networks under layer node-based attack.

Area of Science:

• Complex Networks
• Network Science
• Systems Engineering

Background:

• Multiplex networks, systems with nodes interacting across multiple layers, are prevalent in transportation, infrastructure, and social systems.
• Network robustness, a key area in complex network research, examines system resilience to disruptions.
• Understanding the impact of attacks on multiplex network robustness is crucial but remains an open research question.

Purpose of the Study:

• To analyze the robustness of multiplex networks subjected to layer node-based random or targeted attacks.
• To develop a theoretical framework for predicting the critical threshold and giant component size in attacked multiplex networks.
• To compare the vulnerability of multiplex networks under layer node-based versus multiplex node-based attacks.

Main Methods:

• A theoretical framework was developed to calculate the critical threshold and giant component size.
• Simulations were conducted to validate the theoretical predictions.
• Comparisons were made between layer node-based and multiplex node-based attack strategies.

Main Results:

• The theoretical framework accurately predicts the critical threshold and giant component size, irrespective of the attack strategy (random or targeted).
• Layer node-based attacks render multiplex networks more vulnerable than multiplex node-based attacks.
• This increased vulnerability holds true regardless of the network's average degree or underlying topology.

Conclusions:

• Layer node-based attacks represent a significant threat to the robustness of multiplex networks.
• The developed theoretical framework provides a reliable tool for assessing multiplex network resilience.
• Findings highlight the importance of considering specific attack mechanisms when designing robust complex systems.