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Contribution Details

Type Bachelor's Thesis
Scope Discipline-based scholarship
Title Data Discovery in a DDoS Data Mesh Network
Organization Unit
Authors
  • Tim Portmann
Supervisors
  • Bruno Bastos Rodrigues
  • Katharina Olga Emilia Müller
  • Burkhard Stiller
Language
  • English
Institution University of Zurich
Faculty Faculty of Business, Economics and Informatics
Date 2023
Abstract Text Distributed Denial-of-Service (DDoS) attacks continue to pose a persistent threat in today’s digital landscape. Collaborative defense approaches continuously gain popularity by proposing a distributed defense approach for a distributed attack. Central to such collaborative defense approaches is the exchange of DDoS attack data amongst the parties of the defense architecture. While existing research proposes concepts that enable the collaborative sharing of DDoS information, data-centric solutions remain scarce. Oftentimes, the proposed concepts share a common drawback: Their dependence on specific technologies or hardware that restricts their broad adoption. This thesis aims to propose a data-centric solution that enables decentralized parties in a collaborative DDoS defense architecture to exchange DDoS attack information. The proposed solution utilizes a data mesh network to handle information exchange, complemented by a data discovery service to act upon the exchanged DDoS data. First, extensive research into the subject and tools available to build a DDoS data mesh architecture is explored. Subsequently, a design proposal for the DDoS data mesh architecture, including data discovery capabilities, is described. Based on this design, a DDoS data mesh prototype is implemented and deployed, using the tools explored earlier. Finally, the data mesh is evaluated in regard to its performance and data discovery capabilities. The solution proposed utilizes a technology stack consisting of MySQL instances as DDoS data repositories, Trino as a distributed query engine, and Apache Superset as the data discovery service. This combination enables the efficient exchange and exploration of DDoS data, making it effective for collaborative DDoS defense scenarios and a viable data-centric solution for the exchange of DDoS attack data.
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