Reinforcement learning approach for robustness analysis of complex networks with incomplete information

M Tian, Z Dong, X Wang - Chaos, Solitons & Fractals, 2021 - Elsevier
Network robustness against sequential attacks is significant for complex networks. However,
it is generally assumed that complete information of complex networks is obtained and …

[HTML][HTML] Robustness enhancement of complex networks via No-Regret learning

I Sohn - ICT Express, 2019 - Elsevier
Optimizing complex networks to be resilient against various attack models has been an
important problem that is actively studied in the academia. In the proposed optimization …

Analyzing robustness of complex networks against incomplete information

W Ma, J Fang, J Wu - … Transactions on Circuits and Systems II …, 2022 - ieeexplore.ieee.org
Large scale networked systems are playing an indispensable role in modern society, and
thus the robustness of these systems against random failures or malicious attacks has …

Sequential node attack of complex networks based on Q-learning method

W Ma, J Fang, J Wu - 2021 IEEE International Symposium on …, 2021 - ieeexplore.ieee.org
The security issue of complex network systems, such as communication systems and power
grids, has attracted increasing attention due to cascading failure threats. Many existing …

Sequential defense against random and intentional attacks in complex networks

PY Chen, SM Cheng - Physical Review E, 2015 - APS
Network robustness against attacks is one of the most fundamental researches in network
science as it is closely associated with the reliability and functionality of various networking …

A memetic algorithm for determining the nodal attacks with minimum cost on complex networks

Z Yang, J Liu - Physica A: Statistical Mechanics and its Applications, 2018 - Elsevier
Many real-world networks are exposed in complicated environments and may be destroyed
easily by various kinds of attacks and errors. With no doubt it is of great significance to …

A robust complex network generation method based on neural networks

I Sohn - Physica A: Statistical Mechanics and its Applications, 2019 - Elsevier
To enhance the network tolerance against numerous network attack strategies, various
techniques to optimize conventional complex networks, such as scale-free networks, have …

Multi-node attack strategy of complex networks due to cascading breakdown

F Chaoqi, W Ying, W Xiaoyang, G Yangjun - Chaos, Solitons & Fractals, 2018 - Elsevier
Studying attack strategy of complex networks is the basis of investigating network
characteristics such as robustness, invulnerability, and network security. Knowing means of …

Enhancing the robustness of complex networks against edge-based-attack cascading failures

S Wang, J Liu - 2017 IEEE Congress on Evolutionary …, 2017 - ieeexplore.ieee.org
Existing studies indicated that it is crucial to design network structures with well tolerance
against potential attacks and failures in reality, and several attack models have been …

A learning convolutional neural network approach for network robustness prediction

Y Lou, R Wu, J Li, L Wang, X Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Network robustness is critical for various societal and industrial networks against malicious
attacks. In particular, connectivity robustness and controllability robustness reflect how well a …