Communication publiée dans un ouvrage (Colloques, congrès, conférences scientifiques et actes)
Profiling Smart Contracts Interactions Tensor Decomposition and Graph Mining.
CHARLIER, Jérémy Henri J.; LAGRAA, Sofiane; STATE, Radu et al.
2017In Proceedings of the Second Workshop on MIning DAta for financial applicationS (MIDAS 2017) co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18, 2017.
Peer reviewed
 

Documents


Texte intégral
MIDAS2017_paper7.pdf
Postprint Éditeur (425.47 kB)
Demander un accès

Tous les documents dans ORBilu sont protégés par une licence d'utilisation.

Envoyer vers



Détails



Mots-clés :
Tensor; Graph Mining; Smart Contract
Résumé :
[en] Smart contracts, computer protocols designed for autonomous execution on predefined conditions, arise from the evolution of the Bitcoin’s crypto-currency. They provide higher transaction security and allow economy of scale through the automated process. Smart contracts provides inherent benefits for financial institutions such as investment banking, retail banking, and insurance. This technology is widely used within Ethereum, an open source block-chain platform, from which the data has been extracted to conduct the experiments. In this work, we propose an multi-dimensional approach to find and predict smart contracts interactions only based on their crypto-currency exchanges. This approach relies on tensor modeling combined with stochastic processes. It underlines actual exchanges between smart contracts and targets the predictions of future interactions among the community. The tensor analysis is also challenged with the latest graph algorithms to assess its strengths and weaknesses in comparison to a more standard approach.
Centre de recherche :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Services and Data management research group (SEDAN)
Disciplines :
Sciences informatiques
Auteur, co-auteur :
CHARLIER, Jérémy Henri J. ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
LAGRAA, Sofiane ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
STATE, Radu  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Francois, Jerome;  INRIA Nancy - Grand Est > Madynes
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Profiling Smart Contracts Interactions Tensor Decomposition and Graph Mining.
Date de publication/diffusion :
septembre 2017
Nom de la manifestation :
Second Workshop on MIning DAta for financial applicationS (MIDAS 2017) co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD} 2017)
Organisateur de la manifestation :
ECML PKDD
Lieu de la manifestation :
Skopje, Macédoine
Date de la manifestation :
from 18-09-2017 to 22-09-2017
Manifestation à portée :
International
Titre de l'ouvrage principal :
Proceedings of the Second Workshop on MIning DAta for financial applicationS (MIDAS 2017) co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18, 2017.
Pagination :
31-42
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
URL complémentaire :
Disponible sur ORBilu :
depuis le 06 novembre 2017

Statistiques


Nombre de vues
220 (dont 16 Unilu)
Nombre de téléchargements
4 (dont 3 Unilu)

citations Scopus®
 
5
citations Scopus®
sans auto-citations
5

Bibliographie


Publications similaires



Contacter ORBilu