1. Designing comprehensively robust networks against intentional attacks and cascading failures.
- Author
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Wang, Shuai and Liu, Jing
- Subjects
- *
MALWARE prevention , *SYSTEM failures , *ROBUST control , *MATHEMATICAL optimization , *GENETIC algorithms - Abstract
Highlights • The robustness against malicious attacks and cascading failures are considered simultaneously. • An effective normalized robustness measure has been proposed. • Optimization algorithm based on multi-agent genetic algorithm has been devised and validated. • The obtained results may provide candidates to solve realistic dilemmas as reported in references. Abstract Networked systems exist broadly in daily life and have been greatly emphasized in recent studies. Since these networks are always exposed in complicated environments and may become damaged from different kinds of attacks and failures, including intentional attacks and cascading failures, many researchers have studied the models and mitigation strategies towards these two issues separately. As has been indicated by some reports and materials, the design of comprehensively robust networks against both intentional attacks and cascading failures is of significance in daily life but existing optimization methods seem to be helpless when dealing with this problem. Therefore, this paper focuses on designing such networks. A normalized measure is first designed to evaluate the comprehensive robustness of networks. Then, a multi-agent genetic algorithm is devised to search for robust structures initialized by an input network, termed MAGA-Net R. Combining local and global optima information, the proposed algorithm is validated to be effective on synthetic and real-world networks and to outperform existing optimization methods. The optimal network designed by the proposed algorithm could facilitate theoretical analyses on networked systems and may provide potential candidates to solve some realistic dilemmas. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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