Self-Attentive Models for Real-Time Malware Classification

Self-Attentive Models for Real-Time Malware Classification

Malware classification is a critical task in cybersecurity, as it offers insights into the threats that malware poses to the victim device and helps in the design of countermeasures. For real-time malware classification, due to the high network throughputs of modern networks, there is a challenge of...

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Bibliographic Details
Main Authors:	Qikai Lu, Hongwen Zhang, Husam Kinawi, Di Niu
Format:	Article
Language:	English
Published:	IEEE 2022-01-01
Series:	IEEE Access
Subjects:	Malware classification self-attention networks multi-stage classification cybersecurity
Online Access:	https://ieeexplore.ieee.org/document/9877977/

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