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Analysis of the Matrix Event Graph Replicated Data Type

Jacob, Florian; Beer, Carolin; Henze, Norbert; Hartenstein, Hannes

Abstract (englisch):
Matrix is a new kind of decentralized, topic-based publish-subscribe middleware for communication and data storage that is getting popular particularly as a basis for secure instant messaging. In comparison to traditional decentralized communication systems, Matrix replaces pure message passing with a replicated data structure. This data structure, which we extract and call the Matrix Event Graph (MEG), depicts the causal history of messages. We show that this MEG represents an interesting and important replicated data type for general decentralized applications that are based on causal histories of publish-subscribe events: we show that a MEG possesses strong properties with respect to consistency, byzantine attackers, and scalability. First, we show that the MEG provides Strong Eventual Consistency (SEC), and that it is available under partition, by proving that the MEG is a Conflict-Free Replicated Data Type for causal histories. While strong consistency is impossible here as shown by the famous CAP theorem, SEC is among the best known achievable trade-offs. Second, we discuss the implications of byzantine attackers on the data type's properties. ... mehr

Zugehörige Institution(en) am KIT Fakultät für Informatik (INFORMATIK)
Kompetenzzentrum für angewandte Sicherheitstechnologie (KASTEL)
Institut für Stochastik (STOCH)
Publikationstyp Forschungsbericht/Preprint
Publikationsdatum 12.11.2020
Sprache Englisch
Identifikator KITopen-ID: 1000129941
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