Hunting Traits for Cryptojackers
Gabriel Berecz, Istvan-Gergely Czibula
2019
Abstract
Cryptocurrencies are renowned world wide nowadays and they have been adopted in various industries. This great success comes from both the technology innovation they brought to the world, the blockchain, and the financial opportunities they opened up for investors. One of the unpleasant aspects are the cybercriminals who took advantage of this technology and have developed malicious software (i.e. cryptojacker) in order to gain profit by mining cryptocurrencies on their victims’ personal computer without any consent. This paper proposes to analyze standalone cryptojackers, both statically and dynamically, with the aim of identifying specific traits. The approach draws out features specific to cryptojackers that are selected using statistical methods and explains why a cryptocurrency mining malware has such traits. Based on 20 selected specific features, three different supervised learning classification models have been trained, which are able to differentiate between clean applications and cryptojackers reliably. In experiments, an average accuracy of 92.46% has been achieved.
DownloadPaper Citation
in Harvard Style
Berecz G. and Czibula I. (2019). Hunting Traits for Cryptojackers.In Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 2: SECRYPT, ISBN 978-989-758-378-0, pages 386-393. DOI: 10.5220/0007837403860393
in Bibtex Style
@conference{secrypt19,
author={Gabriel Berecz and Istvan-Gergely Czibula},
title={Hunting Traits for Cryptojackers},
booktitle={Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 2: SECRYPT,},
year={2019},
pages={386-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007837403860393},
isbn={978-989-758-378-0},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 16th International Joint Conference on e-Business and Telecommunications - Volume 2: SECRYPT,
TI - Hunting Traits for Cryptojackers
SN - 978-989-758-378-0
AU - Berecz G.
AU - Czibula I.
PY - 2019
SP - 386
EP - 393
DO - 10.5220/0007837403860393