The Curious Case of Machine Learning in Malware Detection

Sherif Saad, William Briguglio, Haytham Elmiligi

2019

Abstract

In this paper, we argue that detecting malware attacks in the wild is a unique challenge for machine learning techniques. Given the current trend in malware development and the increase of unconventional malware attacks, we expect that dynamic malware analysis is the future for antimalware detection and prevention systems. A comprehensive review of machine learning for malware detection is presented. Then, we discuss how malware detection in the wild present unique challenges for the current state-of-the-art machine learning techniques. We defined three critical problems that limit the success of malware detectors powered by machine learning in the wild. Next, we discuss possible solutions to these challenges and present the requirements of next-generation malware detection. Finally, we outline potential research directions in machine learning for malware detection.

Paper Citation

in Harvard Style

Saad S., Briguglio W. and Elmiligi H. (2019). The Curious Case of Machine Learning in Malware Detection.In Proceedings of the 5th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-359-9, pages 528-535. DOI: 10.5220/0007470705280535

in Bibtex Style

@conference{icissp19,
author={Sherif Saad and William Briguglio and Haytham Elmiligi},
title={The Curious Case of Machine Learning in Malware Detection},
booktitle={Proceedings of the 5th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2019},
pages={528-535},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007470705280535},
isbn={978-989-758-359-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - The Curious Case of Machine Learning in Malware Detection
SN - 978-989-758-359-9
AU - Saad S.
AU - Briguglio W.
AU - Elmiligi H.
PY - 2019
SP - 528
EP - 535
DO - 10.5220/0007470705280535