Towards Scalable Blockchain Analysis
Type de document :
Communication dans un congrès avec actes
Titre :
Towards Scalable Blockchain Analysis
Auteur(s) :
Bragagnolo, Santiago [Auteur]
Analyses and Languages Constructs for Object-Oriented Application Evolution [RMOD]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Marra, Matteo [Auteur]
Polito, Guillermo [Auteur]
Analyses and Languages Constructs for Object-Oriented Application Evolution [RMOD]
École des Mines de Douai [Mines Douai EMD]
Gonzalez Boix, Elisa [Auteur]
Analyses and Languages Constructs for Object-Oriented Application Evolution [RMOD]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Marra, Matteo [Auteur]
Polito, Guillermo [Auteur]
Analyses and Languages Constructs for Object-Oriented Application Evolution [RMOD]
École des Mines de Douai [Mines Douai EMD]
Gonzalez Boix, Elisa [Auteur]
Titre de la manifestation scientifique :
WETSEB 2019 - 2nd International Workshop on Emerging Trends in Software Engineering for Blockchain
Ville :
Montréal
Pays :
Canada
Date de début de la manifestation scientifique :
2019-05-27
Titre de la revue :
WETSWEB '19
Date de publication :
2019-05-27
Mot(s)-clé(s) en anglais :
Blockchain
Smart contracts
Big data
Map/Reduce
Smart contracts
Big data
Map/Reduce
Discipline(s) HAL :
Informatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
Informatique [cs]/Technologies Émergeantes [cs.ET]
Informatique [cs]/Technologies Émergeantes [cs.ET]
Résumé en anglais : [en]
Analysing the blockchain is becoming more and more relevant for detecting attacks and frauds on cryptocurrency exchanges and smart contract activations. However, this is a challenging task due to the continuous growth of ...
Lire la suite >Analysing the blockchain is becoming more and more relevant for detecting attacks and frauds on cryptocurrency exchanges and smart contract activations. However, this is a challenging task due to the continuous growth of the blockchain. For example, in early 2017 Ethereum was estimated to contain approximately 300GB of data [4], a number that keeps growing day after day. In order to analyse such ever-growing amount of data, this paper argues that blockchain analysis should be treated as a novel type of application for Big Data platforms. We also explore the application of parallelization techniques from the Big Data domain, in particular Map/Reduce, to extract and analyse information from the blockchain. We show that our approach significantly improves the index generation by 7.77 times, with a setup of 20 worker nodes, 1 Ethereum node and 1 Database node. We also share our findings of our massively parallel setup for querying Ethereum in terms of architecture and the bottlenecks. This should help researchers setup similar infrastructures for analysing the blockchain in the future.Lire moins >
Lire la suite >Analysing the blockchain is becoming more and more relevant for detecting attacks and frauds on cryptocurrency exchanges and smart contract activations. However, this is a challenging task due to the continuous growth of the blockchain. For example, in early 2017 Ethereum was estimated to contain approximately 300GB of data [4], a number that keeps growing day after day. In order to analyse such ever-growing amount of data, this paper argues that blockchain analysis should be treated as a novel type of application for Big Data platforms. We also explore the application of parallelization techniques from the Big Data domain, in particular Map/Reduce, to extract and analyse information from the blockchain. We show that our approach significantly improves the index generation by 7.77 times, with a setup of 20 worker nodes, 1 Ethereum node and 1 Database node. We also share our findings of our massively parallel setup for querying Ethereum in terms of architecture and the bottlenecks. This should help researchers setup similar infrastructures for analysing the blockchain in the future.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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