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Ivan Pustogarov
Researcher at University of Luxembourg
Publications - 20
Citations - 1435
Ivan Pustogarov is an academic researcher from University of Luxembourg. The author has contributed to research in topics: Anonymity & Service (business). The author has an hindex of 10, co-authored 20 publications receiving 1244 citations. Previous affiliations of Ivan Pustogarov include Russian Academy of Sciences & University of Toronto.
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Proceedings ArticleDOI
Deanonymisation of Clients in Bitcoin P2P Network
TL;DR: In this paper, the authors present an efficient method to deanonymize Bitcoin users, which allows to link user pseudonyms to the IP addresses where the transactions are generated, and also show that a natural countermeasure of using Tor or other anonymity services can be cut-off by abusing anti-DoS countermeasures of the Bitcoin network.
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Deanonymisation of clients in Bitcoin P2P network
TL;DR: This work presents an efficient method to deanonymize Bitcoin users, which allows to link user pseudonyms to the IP addresses where the transactions are generated and shows that a natural countermeasure of using Tor or other anonymity services can be cut-off by abusing anti-DoS countermeasures of the Bitcoin network.
Proceedings ArticleDOI
Trawling for Tor Hidden Services: Detection, Measurement, Deanonymization
TL;DR: Flaws both in the design and implementation of Tor's hidden services are exposed that allow an attacker to measure the popularity of arbitrary hidden services, take down hidden services and deanonymize hidden services.
Proceedings ArticleDOI
Bitcoin over Tor isn't a Good Idea
Alex Biryukov,Ivan Pustogarov +1 more
TL;DR: This paper shows how an attacker can fingerprint users and then recognize them and learn their IP addresses when they decide to connect to the Bit coin network directly.
Proceedings ArticleDOI
Content and Popularity Analysis of Tor Hidden Services
TL;DR: It is found that while the content of Tor hidden services is rather varied, the most popular hidden services are related to botnets, and a method for opportunistic deanonymisation of Tor Hidden Service clients is proposed.