Paper published in a book (Scientific congresses, symposiums and conference proceedings)
Profiling Smart Contracts Interactions Tensor Decomposition and Graph Mining.
Charlier, Jérémy Henri J.; Lagraa, Sofiane; State, Raduet al.
2017 • In 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.
[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.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Services and Data management research group (SEDAN)
Disciplines :
Computer science
Author, co-author :
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
External co-authors :
yes
Language :
English
Title :
Profiling Smart Contracts Interactions Tensor Decomposition and Graph Mining.
Publication date :
September 2017
Event name :
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)
Event organizer :
ECML PKDD
Event place :
Skopje, North Macedonia
Event date :
from 18-09-2017 to 22-09-2017
Audience :
International
Main work title :
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.
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