Distance Metric Learning using Particle Swarm Optimization to Improve Static Malware Detection

Martin Jureček; Róbert Lórencz

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Paper

Distance Metric Learning using Particle Swarm Optimization to Improve Static Malware Detection

Topics: Malware Detection

In Proceedings of the 6th International Conference on Information Systems Security and Privacy ICISSP - Volume 1, 725-732, 2020 , Valletta, Malta

Authors: Martin Jureček and Róbert Lórencz

Affiliation: Faculty of Information Technology, Czech Technical University in Prague, Czech Republic

Keyword(s): Distance Metric Learning, Malware Detection, Static Analysis, Heterogeneous Distance Function, Particle Swarm Optimization, k-Nearest Neighbor.

Abstract: Distance metric learning is concerned with finding appropriate parameters of distance function with respect to a particular task. In this work, we present a malware detection system based on static analysis. We use k-nearest neighbors (KNN) classifier with weighted heterogeneous distance function that can handle nominal and numeric features extracted from portable executable file format. Our proposed approach attempts to specify the weights of the features using particle swarm optimization algorithm. The experimental results indicate that KNN with the weighted distance function improves classification accuracy significantly.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Jureček, M. and Lórencz, R. (2020). Distance Metric Learning using Particle Swarm Optimization to Improve Static Malware Detection. In Proceedings of the 6th International Conference on Information Systems Security and Privacy - ICISSP; ISBN 978-989-758-399-5; ISSN 2184-4356, SciTePress, pages 725-732. DOI: 10.5220/0009180807250732

@conference{icissp20,
author={Martin Jureček. and Róbert Lórencz.},
title={Distance Metric Learning using Particle Swarm Optimization to Improve Static Malware Detection},
booktitle={Proceedings of the 6th International Conference on Information Systems Security and Privacy - ICISSP},
year={2020},
pages={725-732},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009180807250732},
isbn={978-989-758-399-5},
issn={2184-4356},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Information Systems Security and Privacy - ICISSP
TI - Distance Metric Learning using Particle Swarm Optimization to Improve Static Malware Detection
SN - 978-989-758-399-5
IS - 2184-4356
AU - Jureček, M.
AU - Lórencz, R.
PY - 2020
SP - 725
EP - 732
DO - 10.5220/0009180807250732
PB - SciTePress