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Authors: Paul Calderon 1 ; Hirokazu Hasegawa 2 ; Yukiko Yamaguchi 2 and Hajime Shimada 2

Affiliations: 1 Grenoble INP, France ; 2 Nagoya University, Japan

ISBN: 978-989-758-282-0

Keyword(s): Security, Malware, Infection Detection, Machine Learning.

Abstract: One of the major threat in today world are malwares that can infect computers. In order to prevent infection antimalwares softwares are installed but if the malware it is not detected at the installation it will probably never be detected. Behavioural analysis is necessary. Most of nowadays malwares connect to C&C servers by utilizing HTTP or HTTPS in order to receive orders. In this paper a method of behavioural analysis focus on the observation on HTTP and HTTPS network packets will be presented. This analysis is made by using machine learning. We evaluated our method by using 10-fold cross validations. The experimental result shows that precisions and recalls are more than 96% in average.

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Paper citation in several formats:
Calderon P., Hasegawa H., Yamaguchi Y. and Shimada H. (2018). Malware Detection based on HTTPS Characteristic via Machine Learning.In Proceedings of the 4th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-282-0, pages 410-417. DOI: 10.5220/0006654604100417

@conference{icissp18,
author={Paul Calderon and Hirokazu Hasegawa and Yukiko Yamaguchi and Hajime Shimada},
title={Malware Detection based on HTTPS Characteristic via Machine Learning},
booktitle={Proceedings of the 4th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2018},
pages={410-417},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006654604100417},
isbn={978-989-758-282-0},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - Malware Detection based on HTTPS Characteristic via Machine Learning
SN - 978-989-758-282-0
AU - Calderon P.
AU - Hasegawa H.
AU - Yamaguchi Y.
AU - Shimada H.
PY - 2018
SP - 410
EP - 417
DO - 10.5220/0006654604100417

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