Print Email Facebook Twitter Governance of cybersecurity communities Title Governance of cybersecurity communities: Understanding threat intelligence sharing as a collective action problem through incentivization of the National Detection Network Author Bouwman, Xander (TU Delft Technology, Policy and Management) Contributor van Eeten, M.J.G. (mentor) Warnier, Martijn (graduation committee) Degree granting institution Delft University of Technology Programme Complex Systems Engineering and Management (CoSEM) Date 2018-09-25 Abstract Organizations benefit from improved cybersecurity threat detection capabilities if they share information in a community of their peers. However, organizations are unlikely to share the sensitive information that is most valuable as this poses individual risks. Information sharing in cybersecurity communities therefore forms a collective action problem. Currently, cybersecurity information sharing is being studied primarily as a technological challenge. Drawing on theory from economics and the social sciences, this study proposes governance requirements to overcome individual interests and improve information sharing. These are used to design a governance structure for the case of the National Detection Network, a cybersecurity community initiated by the government of the Netherlands. The proposed governance meets interests of parties through a process of interactive decision-making in four phases, while incentivizing sharing of cybersecurity information. Lessons are drawn from the case for cybersecurity communities in general. Subject threat intelligencecollective actionincentivesnational detection networkinformation sharingthreat detectioninteractive decision makingcybersecurity communitiesprocess design To reference this document use: http://resolver.tudelft.nl/uuid:3134a935-1156-409d-a58c-47cf06a88dad Part of collection Student theses Document type master thesis Rights © 2018 Xander Bouwman Files PDF Governance_of_cybersecuri ... n_2018.pdf 1.13 MB Close viewer /islandora/object/uuid:3134a935-1156-409d-a58c-47cf06a88dad/datastream/OBJ/view