Ethereum’s Peer-to-Peer Network Monitoring and Sybil Attack Prevention - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue Journal of Network and Systems Management Année : 2022

Ethereum’s Peer-to-Peer Network Monitoring and Sybil Attack Prevention

Résumé

Public blockchains, like Ethereum, rely on an underlying peer-to-peer (P2P) network to disseminate transactions and blocks between nodes. With the rise of blockchain applications and cryptocurrencies values, they have become critical infrastructures which still lack comprehensive studies. In this paper, we propose to investigate the reliability of the Ethereum P2P network. We developed our own dependable crawler to collect information about the peers composing the network. Our data analysis regarding the geographical distribution of peers and the churn rate shows good network properties while the network can exhibit a sudden and major increase in size and peers are highly concentrated on a few ASes. In a second time, we investigate suspicious patterns that can denote a Sybil attack. We find that many nodes hold numerous identities in the network and could become a threat. To mitigate future Sybil attacks, we propose an architecture to detect suspicious nodes and revoke them. It is based on a monitoring system, a smart contract to propagate the information and an external revocation tool to help clients remove their connections to suspicious peers. Our experiment on Ethereum's Test network proved that our solution is effective.
Fichier principal
Vignette du fichier
jnsm2022.pdf (451.21 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03777454 , version 1 (14-09-2022)

Identifiants

Citer

Jean-Philippe Eisenbarth, Thibault Cholez, Olivier Perrin. Ethereum’s Peer-to-Peer Network Monitoring and Sybil Attack Prevention. Journal of Network and Systems Management, 2022, Special Issue on Blockchains and Distributed Ledgers in Network and Service Management, 30 (4), pp.65. ⟨10.1007/s10922-022-09676-2⟩. ⟨hal-03777454⟩
171 Consultations
1368 Téléchargements

Altmetric

Partager

More