KIT | KIT-Bibliothek | Impressum | Datenschutz

Exploiting Transaction Accumulation and Double Spends for Topology Inference in Bitcoin

Grundmann, Matthias ORCID iD icon 1; Neudecker, Till 1; Hartenstein, Hannes 1
1 Institut für Telematik (TM), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Bitcoin relies on a peer-to-peer network for communication between participants. Knowledge of the network topology is of scientific interest but can also facilitate attacks on the users’ anonymity and the system’s availability. We present two approaches for inferring the network topology and evaluate them in simulations and in real-world experiments in the Bitcoin testnet. The first approach exploits the accumulation of multiple transactions before their announcement to other peers. Despite the general feasibility of the approach, simulation and experimental results indicate a low inference quality. The second approach exploits the fact that double spending transactions are dropped by clients. Experimental results show that inferring the neighbors of a specific peer is possible with a precision of 71 % and a recall of 87 % at low cost.

Postprint §
DOI: 10.5445/IR/1000086906/post
Veröffentlicht am 11.02.2020
DOI: 10.1007/978-3-662-58820-8_9
Zitationen: 16
Zitationen: 25
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Telematik (TM)
Kompetenzzentrum für angewandte Sicherheitstechnologie (KASTEL)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 02.03.2019
Sprache Englisch
Identifikator ISBN: 978-3-662-58819-2
ISSN: 0302-9743
KITopen-ID: 1000086906
Erschienen in Financial Cryptography and Data Security : FC 2018 International Workshops, BITCOIN, VOTING, and WTSC, (FC 2018), Nieuwpoort, CU, March 2, 2018. Ed.: A. Zohar
Verlag Springer Verlag
Seiten 113-126
Serie Security and Cryptology ; 10958
Projektinformation KASTEL_IoE (BMBF, 16KIS0346)
Vorab online veröffentlicht am 10.02.2019
Schlagwörter kastel, kastel-ioe
Nachgewiesen in Dimensions
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page