Application of Distance Metric Learning to Automated Malware Detection

Application of Distance Metric Learning to Automated Malware Detection

Distance metric learning aims to find the most appropriate distance metric parameters to improve similarity-based models such as <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-Nearest Neighbors or <inline-formula> <tex-math not...

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Bibliographic Details
Main Authors: Martin Jurecek, Robert Lorencz
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Distance metric learning
malware detection
particle swarm optimization
<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">k</italic>-nearest neighbors
Online Access:https://ieeexplore.ieee.org/document/9469874/

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https://ieeexplore.ieee.org/document/9469874/

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