Vitenskapelig artikkel   2021

Boudko, Svetlana; Abie, Habtamu; Boscolo, Mirna; Ferrario, Davide

Publikasjonsdetaljer

Tidsskrift:

Lecture Notes in Electrical Engineering, 2021

Utgiver:

Springer

Internasjonale standardnumre:

Trykt: 1876-1100
Elektronisk: 1876-1119

Lenker:

DOI: doi.org/10.1007/978-981-33-6385-4

The blockchain and Peer-To-Peer Payment solutions become adopted by financial institutions. While these changes bring significant service benefits they also increase the risks and vulnerabilities of the financial services. In this paper, we investigate, develop, and evaluate machine learning (ML) algorithms for predicting attacks on blockchain nodes and a Peer to Peer payment system. We have evaluated a set of machine learning algorithms that include classifica-tion ML algorithms from the scikit-learn library. We demonstrate that the pro-posed solution is able to predict cyber-physical attacks close to 100% accuracy. We have implemented a service prototype as a proof of concept. The prediction is done based on the collected data of the blockchain and peer-to-peer payment nodes. For the evaluation of the algorithms, a set of highly reputable classifica-tion metrics has been selected and applied.