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/

Internet

https://ieeexplore.ieee.org/document/9877977/

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