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SUMMARY
Contemporary society increasingly depends on complex systems such as the Internet, traffic, electrical power grids, social networks, ecological networks and so on. Due to the importance of these systems, the complex networks which are used to model them have been receiving much interest from multiple disciplines of the research community. Despite progress on several fronts, many crucial aspects of complex networks are not yet sufficiently understood. One of these aspects is the robustness of these systems to random failure and malicious attacks.
The goal of this project is to optimise model networks in a dynamical process, changing their topology in the search for robust structures which can withstand malicious attacks. The project’s applications will be of special interest to epidemiologists who want to break up disease transmission networks by targeted vaccinations and to police forces when disrupting criminal networks.
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SOLUTIONS
- Utilising Monte-Carlo based optimization technique as well as novel, bioinspired optimization processes such as the evolutionary modification of populations of networks
- Developing generally applicable methods for enhancing robustness based on the connection between the network’s topology and its resilience to malicious attacks
- Using the tools for network optimisation to devolvop strategies for social, and in particular criminal, network disruption
- Adopting fragmentation optimisation an inverse robustness optimisation simulation methods to develop efficient attack strategies and to learn how to immunise and protect benign networks
- Applying the found strategies to disrupt real world criminal networks in collaboration with the federal police forces
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LINK: http://p3.snf.ch/project-126853
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